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Accurate technique for complete geometric calibration of cone-beam computed tomography systems
Abstract
Cone-beam computed tomography systems have been developed to provide in situ imaging for the purpose of guiding radiation therapy. Clinical systems have been constructed using this approach, a clinical linear accelerator (Elekta Synergy RP) and an iso-centric C-arm. Geometric calibration involves the estimation of a set of parameters that describes the geometry of such systems, and is essential for accurate image reconstruction. We have developed a general analytic algorithm and corresponding calibration phantom for estimating these geometric parameters in cone-beam computed tomography (CT) systems. The performance of the calibration algorithm is evaluated and its application is discussed. The algorithm makes use of a calibration phantom to estimate the geometric parameters of the system. The phantom consists of 24 steel ball bearings (BBs) in a known geometry. Twelve BBs are spaced evenly at 30 deg in two plane-parallel circles separated by a given distance along the tube axis. The detector (e.g., a flat panel detector) is assumed to have no spatial distortion. The method estimates geometric parameters including the position of the x-ray source, position, and rotation of the detector, and gantry angle, and can describe complex source-detector trajectories. The accuracy and sensitivity of the calibration algorithm was analyzed. The calibration algorithm estimates geometric parameters in a high level of accuracy such that the quality of CT reconstruction is not degraded by the error of estimation. Sensitivity analysis shows uncertainty of 0.01 degrees (around beam direction) to 0.3 degrees (normal to the beam direction) in rotation, and 0.2 mm (orthogonal to the beam direction) to 4.9 mm (beam direction) in position for the medical linear accelerator geometry. Experimental measurements using a laboratory bench Cone-beam CT system of known geometry demonstrate the sensitivity of the method in detecting small changes in the imaging geometry with an uncertainty of 0.1 mm in transverse and vertical (perpendicular to the beam direction) and 1.0 mm in the longitudinal (beam axis) directions. The calibration algorithm was compared to a previously reported method, which uses one ball bearing at the isocenter of the system, to investigate the impact of more precise calibration on the image quality of cone-beam CT reconstruction. A thin steel wire located inside the calibration phantom was imaged on the conebeam CT lab bench with and without perturbations in source and detector position during the scan. The described calibration method improved the quality of the image and the geometric accuracy of the object reconstructed, improving the full width at half maximum of the wire by 27.5% and increasing contrast of the wire by 52.8%. The proposed method is not limited to the geometric calibration of cone-beam CT systems but can be used for many other systems, which consist of one or more point sources and area detectors such as calibration of megavoltage (MV) treatment system (focal spot movement during the beam delivery, MV source trajectory versus gantry angle, the axis of collimator rotation, and couch motion), cross calibration between Kilovolt imaging and MV treatment system, and cross calibration between multiple imaging systems. Using the complete information of the system geometry, it was demonstrated that high image quality in CT reconstructions is possible even in systems with large geometric nonidealities.
... Offline methods perform the calibration for a given scanning protocol during system servicing and save the geometry data for subsequent use. [35][36][37][38][39][40][41] Offline methods thus assume that the scanning orbit for the calibrated protocol is highly reproducible. Online methods treat each scan as a new calibration task and therefore are suitable for irreproducible scanning orbits. ...
... Fiducial-based methods localize the 2D coordinates of fiducial markers from the projection images and perform calibration-related calculations only on the coordinates. 26,35,36,40,42,[46][47][48][49][50][51] These operations are typically less computationally intensive than image-based methods, but the existing methods typically assume accurate localization of fiducials in projection images, which may be difficult when the background is complex. Methods using a known target assume that the 3D structure of the imaging target is precisely known a priori, for example, from a digital model or prior scans, as is the case with aforementioned dedicated calibration phantoms and 3D-2D registration methods. ...
... Two widely used fiducial configurations were adopted:spiral 36,37 and double rings. 35,40 The spiral configuration wrapped around the cylinder twice (Figures 3c,e). The double ring configuration included five fiducials per ring and two fiducials near the center and on the opposite sides of the phantom (Figures 3d,f ). ...
Background
Cone‐beam CT (CBCT) with non‐circular scanning orbits can improve image quality for 3D intraoperative image guidance. However, geometric calibration of such scans can be challenging. Existing methods typically require a prior image, specialized phantoms, presumed repeatable orbits, or long computation time.
Purpose
We propose a novel fully automatic online geometric calibration algorithm that does not require prior knowledge of fiducial configuration. The algorithm is fast, accurate, and can accommodate arbitrary scanning orbits and fiducial configurations.
Methods
The algorithm uses an automatic initialization process to eliminate human intervention in fiducial localization and an iterative refinement process to ensure robustness and accuracy. We provide a detailed explanation and implementation of the proposed algorithm. Physical experiments on a lab test bench and a clinical robotic C‐arm scanner were conducted to evaluate spatial resolution performance and robustness under realistic constraints.
Results
Qualitative and quantitative results from the physical experiments demonstrate high accuracy, efficiency, and robustness of the proposed method. The spatial resolution performance matched that of our existing benchmark method, which used a 3D‐2D registration‐based geometric calibration algorithm.
Conclusions
We have demonstrated an automatic online geometric calibration method that delivers high spatial resolution and robustness performance. This methodology enables arbitrary scan trajectories and should facilitate translation of such acquisition methods in a clinical setting.
... These two beads, with the distance between them known precisely, trace out two elliptical figures on the detector when the phantom is rotated, and from the parametric description of these ellipses, the calibration alignment parameters can be determined analytically using explicit formulae. The most widely used phantom types consist of beads in a line (Smekal et al 2004, Yang et al 2006, Xu and Tsui 2012, 2013, helical (Hoppe et al 2007, Xu et al 2014, circular (Cho et al 2005, Ford et al 2011, Yang et al 2017, or other special arrangements (Mennessier et al 2009, Li et al 2010. The phantom with beads arranged helically is well suited for a C-arm CBCT system (Hoppe et al 2007). ...
... The phantom with beads arranged helically is well suited for a C-arm CBCT system (Hoppe et al 2007). The phantom with beads arranged circularly needs precise knowledge of the locations of the beads to get accurate geometric parameters (Cho et al 2005, Yang et al 2017. The complete set of geometric calibration parameters can be obtained from the traces of the beads on the detector, such as ellipses, to estimate the misalignment of the detector. ...
... The method of Yang et al can be applied to non-ideal circular motion and have the calibration for each projection. One of the important things was not mentioned in their paper, but it showed in the previous work (Cho et al 2005), 'the axis of phantom need be coincident with the AOR'. It is difficult to set up those two axes together. ...
Cone-beam Computed Tomography (CBCT) is widely used in dental imaging, small animal imaging, radiotherapy, and non-destructive industrial inspection. The quality of CBCT images depends on the precise knowledge of the CBCT system’s alignment. We introduce a distinct procedure, “precision alignment loop (PAL)”, to calibrate any CBCT system with a circular trajectory. We describe the calibration procedure by using a line-beads phantom, and how PAL determines the misalignments from a CBCT system. PAL also yields the uncertainties in the simulated calibration to give an estimate of the errors in the misalignments. From the analytical simulations, PAL can precisely obtain the source-to-rotation axis distance (SRD), and the geometric center G, “the point in z-axis meets the detector”, where the z-axis is coincident with the line from the X-ray source that intersects the axis of the rotation (AOR) orthogonally. The uncertainties of three misalignment angles of the detector are within ±0.05°, which is close to ±0.04° for the results of Yang et al. [18], but our method is easy and simple to implement. Our distinct procedure, on the other hand, yields the calibration of a micro-CT system and an example of reconstructed images, showing our calibration method for the CBCT system to be simple, precise, and accurate.
... Similar to calibration, geometric corrections also exist 2 after acquisition and CT reconstruction [17]. System variables for geometric calibration include the x-ray source position; detector position, tilt, and rotation; and piercing point, where the piercing point is the projection of the world coordinate system origin onto the detector coordinate system [13]. Consequently, the system may be reduced to 11 independent variables. ...
... This is made complicated by an engineering trade-off regarding constellation size. Large constellations are used for the calibration of conventional CT systems because they provide superior geometric accuracy [12], [13]. However, for the open configuration CT system described here, placing large constellations in every x-ray shot will interfere with the inspection of the region of interest. ...
... To determine the geometry for every shot, the geometry problem may be cast into an optimization problem to reduce a cost function for the purposes of matching projected marker centers to the x-ray image, which is a similar strategy to [12], [13]. Unfortunately, solving this optimization problem with nine system unknowns is difficult since the solution space has multiple minima. ...
Open-configuration portable x-ray computed tomography (CT) is a technology that enables the volumetric inspections of regions of interest on large parts. The open-configuration aspect of x-ray CT allows it to be portable and applicable to large and irregular parts that are not conducive to conventional CT booth setups or ring geometry. The inherent problem with the open-configuration setup is lack of mechanical controls that determine the geometry between the x-ray source, detector, and part. As a result, the focus of this paper is a prerequisite technique to self-determine the x-ray shot geometry from the x-ray shot itself. Additional difficulties pertaining to self-determined shot geometry is that there are nine system unknowns for every x-ray shot as compared to conventional CT that has nine system unknowns total. To address these problems, the technique presented here has three unique features: 1) it consists of only a few known constellation markers, 2) it exploits geometry to break the problem into many to find the global optimum solution, and 3) it reprojects a 3D model of the reference constellation for final geometry refinement. A comparison study is provided to demonstrate the advantages of this solution over random basin hopping, a general purpose global optimization technique. After performing this process for every shot, results show that the geometric error is satisfactorily low for successful CT reconstruction.
... Offline calibration methods apply to both regular [33][34][35][36][37][38] and irregular acquisition geometries. [39][40][41][42] For the systems with a regular acquisition geometry, a simple phantom, for example, with one or several ball bearings (BBs) embedded in is enough to obtain all geometric parameters 23,34 since the parameter number is very few. In those calibration cases, phantoms are not sophisticated and can be made easily by hand, and, therefore, the corresponding methods are very convenient to use. ...
... 33,34,38 For the irregular systems whose geometric parameters for each view are variant, a simple phantom without any precision requirement cannot work. Because the full projection matrix is not solvable unless some extra conditions are given, for example, the spatial relationship between point markers 39,[42][43][44][45][46] or line markers 40,41 in the phantom. To the best of our knowledge, most of the literature assumes that the geometric relationship of the markers is precisely known. ...
... To the best of our knowledge, most of the literature assumes that the geometric relationship of the markers is precisely known. Some of these methods depend on dedicatedly fabricated phantoms in which fiducials are precisely assembled in some specific pattern, such as a helix, 46 circles, 42,45 or orthogonal lines. 39 The geometry of a specific pattern is treated as a known condition, and hence fabrication accuracy is a key prerequisite for obtaining accurate geometric parameters. ...
Background
Many dedicated cone‐beam CT (CBCT) systems have irregular scanning trajectories. Compared with the standard CBCT calibration, accurate calibration for CBCT systems with irregular trajectories is a more complex task, since the geometric parameters for each scanning view are variable. Most of the existing calibration methods assume that the intrinsic geometric relationship of the fiducials in the phantom is precisely known, and rarely delve deeper into the issue of whether the phantom accuracy is adapted to the calibration model.
Purpose
A high‐precision phantom and a highly robust calibration model are interdependent and mutually supportive, and they are both important for calibration accuracy, especially for the high‐resolution CBCT. Therefore, we propose a calibration scheme that considers both accurate phantom measurement and robust geometric calibration.
Methods
Our proposed scheme consists of two parts: (1) introducing a measurement model to acquire the accurate intrinsic geometric relationship of the fiducials in the phantom; (2) developing a highly noise‐robust nonconvex model‐based calibration method. The measurement model in the first part is achieved by extending our previous high‐precision geometric calibration model suitable for CBCT with circular trajectories. In the second part, a novel iterative method with optimization constraints based on a back‐projection model is developed to solve the geometric parameters of each view.
Results
The simulations and real experiments show that the measurement errors of the fiducial ball bearings (BBs) are within the subpixel level. With the help of the geometric relationship of the BBs obtained by our measurement method, the classic calibration method can achieve good calibration based on far fewer BBs. All metrics obtained in simulated experiments as well as in real experiments on Micro CT systems with resolutions of 9 and 4.5 μm show that the proposed calibration method has higher calibration accuracy than the competing classic method. It is particularly worth noting that although our measurement model proves to be very accurate, the classic calibration method based on this measurement model can only achieve good calibration results when the resolution of the measurement system is close to that of the system to be calibrated, but our calibration scheme enables high‐accuracy calibration even when the resolution of the system to be calibrated is twice that of the measurement system.
Conclusions
The proposed combined geometrical calibration scheme does not rely on a phantom with an intricate pattern of fiducials, so it is applicable in Micro CT with high resolution. The two parts of the scheme, the “measurement model” and the “calibration model,” prove to be of high accuracy. The combination of these two models can effectively improve the calibration accuracy, especially in some extreme cases.
... This requirement is necessitated by varying factors, such as speed-up and slow-down at the beginning and end of scanning, the desired acquisition speed and angular spacing, the detector read out speed or projections per second, pixel binning, and C-arm trajectory. Generally, geometric calibration takes one of two approaches: an analytic approach that explicitly describes all required system parameters for image reconstruction [48][49][50][51][52][53][54][55] and the pose determination approach 56-62 that describes all system parameters in a calibration matrix containing extrinsic and intrinsic parameters. The pose consists of the angular position ( , , ) and possible translation (T) of the system: factors commonly referred to as "extrinsic parameters." ...
... system's "intrinsic parameters". 48,59,60,63,64 Due to the small changes in the source and detector positions that may occur during the rotation of C-arm CBCT systems, the source and detector positions (and their relationships to each other) are considered intrinsic parameters, unlike in the conventional pin-hole camera definition of extrinsic and intrinsic parameters. ...
... Although these parameters can be estimated from projection matrices, as used in pose determination, the results can be unstable due in part to the challenges of estimating the source to detector distance (which can vary due to minor instabilities) from the projection matrices. 48 The methods suggested in the literature range in their approaches and mathematical formulation, but they are founded in geometrical descriptions relating the 3D position of the physical phantom to the measured image of the phantom at the detector. They can be broadly classified into two approaches, those based on non-linear optimization 65,66 and those based on a direct analytical solution. ...
This report reviews the image acquisition and reconstruction characteristics of C‐arm Cone Beam Computed Tomography (C‐arm CBCT) systems and provides guidance on quality control of C‐arm systems with this volumetric imaging capability. The concepts of 3D image reconstruction, geometric calibration, image quality, and dosimetry covered in this report are also pertinent to CBCT for Image‐Guided Radiation Therapy (IGRT). However, IGRT systems introduce a number of additional considerations, such as geometric alignment of the imaging at treatment isocenter, which are beyond the scope of the charge to the task group and the report.
Section 1 provides an introduction to C‐arm CBCT systems and reviews a variety of clinical applications. Section 2 briefly presents nomenclature specific or unique to these systems. A short review of C‐arm fluoroscopy quality control (QC) in relation to 3D C‐arm imaging is given in Section 3. Section 4 discusses system calibration, including geometric calibration and uniformity calibration. A review of the unique approaches and challenges to 3D reconstruction of data sets acquired by C‐arm CBCT systems is give in Section 5. Sections 6 and 7 go in greater depth to address the performance assessment of C‐arm CBCT units. First, Section 6 describes testing approaches and phantoms that may be used to evaluate image quality (spatial resolution and image noise and artifacts) and identifies several factors that affect image quality. Section 7 describes both free‐in‐air and in‐phantom approaches to evaluating radiation dose indices.
The methodologies described for assessing image quality and radiation dose may be used for annual constancy assessment and comparisons among different systems to help medical physicists determine when a system is not operating as expected. Baseline measurements taken either at installation or after a full preventative maintenance service call can also provide valuable data to help determine whether the performance of the system is acceptable. Collecting image quality and radiation dose data on existing phantoms used for CT image quality and radiation dose assessment, or on newly developed phantoms, will inform the development of performance criteria and standards. Phantom images are also useful for identifying and evaluating artifacts. In particular, comparing baseline data with those from current phantom images can reveal the need for system calibration before image artifacts are detected in clinical practice. Examples of artifacts are provided in Sections 4, 5, and 6.
... For offline methods, researchers use a precisely designed phantom with known spatial information to estimate the errors in geometric parameters and then calibrate the geometry either through adjustment of mechanical equipment or accounting for errors with reconstruction algorithms. For example, Cho et al. 13 used 24 steel beads as a phantom to get a set of projections for parameter estimation. Yang et al. 14 reduced the phantom to 12 steel beads on two planes in a cylinder phantom for error assessment. ...
... However, due to the parallel nature of the detected edges, under some special conditions, our proposed line conditions may encounter a limitation. That is, in Equations (10)- (13), when and are equal to zero, variable n will be eliminated from the formula, leading to n being unsolvable. Therefore, we propose adding an extra condition to assist in solving the problem. ...
... where RHS i is the corresponding right-hand side part in Equations (10)- (13). A gradient-free algorithm, the Nelder-Mead simplex method, 28 is employed to find the optimized value of the remaining m, , parameters starting from zero initialization. ...
Background
Computed tomography (CT) generates a three‐dimensional rendering that can be used to interrogate a given region or desired structure from any orientation. However, in preclinical research, its deployment remains limited due to relatively high upfront costs. Existing integrated imaging systems that provide merged planar X‐ray also dwarfs CT popularity in small laboratories due to their added versatility.
Purpose
In this paper, we sought to generate CT‐like data using an existing small‐animal X‐ray imager with a specialized specimen rotation system, or MiSpinner. This setup conforms to the cone‐beam CT (CBCT) geometry, which demands high spatial calibration accuracy. Therefore, a simple but robust geometry calibration algorithm is necessary to ensure that the entire imaging system works properly and accurately.
Methods
Because the rotation system is not permanently affixed, we propose a structure tensor‐based two‐step online (ST‐TSO) geometry calibration algorithm. Specifically, two datasets are needed, namely, calibration and actual measurements. A calibration measurement detects the background of the system forward X‐ray projections. A study on the background image reveals the characteristics of the X‐ray photon distribution, and thus, provides a reliable estimate of the imaging geometry origin. Actual measurements consisted of an X‐ray of the intended object, including possible geometry errors. A comprehensive image processing technique helps to detect spatial misalignment information. Accordingly, the first processing step employs a modified projection matrix‐based calibration algorithm to estimate the relevant geometric parameters. Predicted parameters are then fine‐tuned in a second processing step by an iterative strategy based on the symmetry property of the sum of projections. Virtual projections calculated from the parameters after two‐step processing compensate for the scanning errors and are used for CT reconstruction. Experiments on phantom and mouse imaging data were performed to validate the calibration algorithm.
Results
Once system correction was conducted, CBCT of a CT bar phantom and a cohort of euthanized mice were analyzed. No obvious structure error or spatial artifacts were observed, validating the accuracy of the proposed geometry calibration method. Digital phantom simulation indicated that compared with the preset spatial values, errors in the final estimated parameters could be reduced to 0.05° difference in dominant angle and 0.5‐pixel difference in dominant axis bias. The in‐plane resolution view of the CT‐bar phantom revealed that the resolution approaches 150 μ$\umu$m.
Conclusions
A constrained two‐step online geometry calibration algorithm has been developed to calibrate an integrated X‐ray imaging system, defined by a first‐step analytical estimation and a second‐step iterative fine‐tuning. Test results have validated its accuracy in system correction, thus demonstrating the potential of the described system to be modified and adapted for preclinical research.
... Two general classes of approaches can be identified: those based on precisely defined or known marker assemblies [154,152,26,126,173,20,177,206,69,108,78,153,112,96,40,204,213], which allow calibration on a per-view basis, and those working with fiducials of unknown placement yet requiring precise circular motion of these markers throughout a tomographic scan [55,95,130,172,206,187,198,52,157,203,94] (with some of these assuming the distances between markers known [130,206,187,198,203]). While the former methods are typically used for macroscopic systems with fields of view in the range of 10 cm and larger, the latter are required for microscopic systems for which the manufacturing of well-defined calibration phantoms is hard to impossible. ...
... An additional distinction can be made from the technical point of view of system parametrization: methods aiming to determine the projective mapping from 3D to 2D space in terms of a projection matrix that is consistent with the available observations irrespective of the question how the particular mapping arises physically [154,126,173,177,69,96], and methods aiming to relate projections or properties thereof to real space geometry parameters (relative distances and orientation angles of source and detector) [55,95,154,152,130,9,172,20,206,108,78,153,112,40,198,52,157,203,204,94]. Differences also exist in the evaluation of the projection data used for calibration: methods directly working on extracted projection samples (2D points) without further data reduction or interpretation [55,95,154,26,126,9,173,69,108,157,213,94], as well as methods reducing the observed projections by means of matching them to an expected model (such as e.g. ...
... Differences also exist in the evaluation of the projection data used for calibration: methods directly working on extracted projection samples (2D points) without further data reduction or interpretation [55,95,154,26,126,9,173,69,108,157,213,94], as well as methods reducing the observed projections by means of matching them to an expected model (such as e.g. elliptic trajectories) or otherwise exploiting specific geometric features of the utilized calibration structure [152,130,172,20,177,206,78,153,112,40,198,52,203,204]. Calibration methods may further be characterized based on their core calibration approaches: [154,126,173,177,69,96] reduce the calibration problem to the solution of a linear system of equations in a least squares sense e.g. by means of singular value decomposition (requiring the imaged object to be known). ...
X-ray dark-field imaging allows to resolve the conflict between the demand for centimeter scaled fields of view and the spatial resolution required for the characterization of fibrous materials structured on the micrometer scale. It draws on the ability of X-ray Talbot interferometers to provide full field images of a sample's ultra small angle scattering properties, bridging a gap of multiple orders of magnitude between the imaging resolution and the contrasted structure scale. The correspondence between shape anisotropy and oriented scattering thereby allows to infer orientations within a sample's microstructure below the imaging resolution. First demonstrations have shown the general feasibility of doing so in a tomographic fashion, based on various heuristic signal models and reconstruction approaches. Here, both a verified model of the signal anisotropy and a reconstruction technique practicable for general imaging geometries and large tensor valued volumes is developed based on in-depth reviews of dark-field imaging and tomographic reconstruction techniques. To this end, a wide interdisciplinary field of imaging and reconstruction methodologies is revisited. To begin with, a novel introduction to the mathematical description of perspective projections provides essential insights into the relations between the tangible real space properties of cone beam imaging geometries and their technically relevant description in terms of homogeneous coordinates and projection matrices. Based on these fundamentals, a novel auto-calibration approach is developed, facilitating the practical determination of perspective imaging geometries with minimal experimental constraints. A corresponding generalized formulation of the widely employed Feldkamp algorithm is given, allowing fast and flexible volume reconstructions from arbitrary tomographic imaging geometries. Iterative reconstruction techniques are likewise introduced for general projection geometries, with a particular focus on the efficient evaluation of the forward problem associated with tomographic imaging. A highly performant 3D generalization of Joseph's classic linearly interpolating ray casting algorithm is developed to this end and compared to typical alternatives. With regard to the anisotropic imaging modality required for tensor tomography, X-ray dark-field contrast is extensively reviewed. Previous literature is brought into a joint context and nomenclature and supplemented by original work completing a consistent picture of the theory of dark-field origination. Key results are explicitly validated by experimental data with a special focus on tomography as well as the properties of anisotropic fibrous scatterers. In order to address the pronounced susceptibility of interferometric images to subtle mechanical imprecisions, an efficient optimization based evaluation strategy for the raw data provided by Talbot interferometers is developed. Finally, the fitness of linear tensor models with respect to the derived anisotropy properties of dark-field contrast is evaluated, and an iterative scheme for the reconstruction of tensor valued volumes from projection images is proposed. The derived methods are efficiently implemented and applied to fiber reinforced plastic samples, imaged at the ID19 imaging beamline of the European Synchrotron Radiation Facility. The results represent unprecedented demonstrations of X-ray dark-field tensor tomography at a field of view of 3-4cm, revealing local fiber orientations of both complex shaped and low-contrast samples at a spatial resolution of 0.1mm in 3D. The results are confirmed by an independent micro CT based fiber analysis.
... In [10] the authors propose a calibration method based on a cylindrical calibration phantom similar to what we will use here. At least two sets of spheres in a circular arrangement are needed in order for this approach to work because this allows the extraction of the center of the calibration phantom's coordinate system. ...
... In [11] the authors propose a method similar to [10]. A calibration phantom with two sets of spheres that are arranged in an ellipse is used. ...
... A calibration phantom with two sets of spheres that are arranged in an ellipse is used. The difference to [10] is that the geometric parameters are not calculated directly but an optimization step is introduced for computing the rotation parameters. Additionally, this method is valid for arbitrary geometries, not just rotational trajectories compared to [10]. ...
We present an X-ray Computed Tomography setup that integrates a seven degrees of freedom robotic arm as a sample holder within an existing laboratory X-ray computed tomography setup. We aim to provide a flexible sample holder that is able to execute non-standard and task-specific trajectories for complex samples. The robotic arm is integrated with a unified software package that allows for path planning, collision detection, geometric calibration and reconstruction of the sample. The calibration is necessary to identify the accurate pose of the sample which deviates from the expected pose due to inaccurate placement of the robotic arm. With our software the user is able to command the robotic arm to execute arbitrary trajectories for a given sample in a safe manner and output its reconstruction to the user. We present experimental results with a circular trajectory where the robotic sample holder achieves identical visual quality compared to a conventional sample holder.
... To achieve calibration, phantoms are manufactured to precise dimensions, which usually include a point-like marker (spherical shape) within a cylindrical object. Several phantom geometries and models are given in the literature that have proven successful in achieving quality magnification corrections [41][42][43][44][45][46][47][48][49]. For those methods employing steel spheres in their phantoms, the first challenge is locating the center of projection on the detector image [49,50]. ...
... For those methods employing steel spheres in their phantoms, the first challenge is locating the center of projection on the detector image [49,50]. To get the best estimation of the location and edges, the number of spherical balls within phantoms increased through time, starting with a phantom of two spherical markers up to more than 150 [43,45,48,51,52]. Moreover, in many cases the projection was considered to be ellipse-like. ...
... In general, calibration techniques can be divided into two main categories which include the techniques using a calibration phantom [2-4, 9, 11] and self-calibration methods [6,12] that exploit the acquired radiographs of the target objects for calculating the geometry parameters of their acquisition systems. Most X-ray CT calibration methods that rely on a phantom, require specifically-designed and/or expensive phantoms with marker features placed at accurately-known positions in the bearing structures and measured precisely using Coordinate Measuring Machines (CMM) which are often not available in most X-ray imaging laboratories [3,4,9]. Among them, Liu et al. [9] introduced a phantom that carried 12-sphere Zirconia markers placed on a triple helix glass structure. ...
... Furthermore, the phantom was built from made-to-order components, and hence not always easily available. Another well-designed phantom was presented by Cho et al. and Chetley et al. [3,4] and featured two circular rings of regular placed steel balls carried on an acrylic cylinder. Both the diameters of the supporting cylinder and the steel balls were measured in advance. ...
Knowledge of the acquisition geometry is key for tomographic reconstruction. Before image reconstruction algorithms can be applied to compute a 3D image from a set of 2D projections, calibration must be carried out to correct geometrical inaccuracies. The main source of geometric misalignment can be attributed to possible mechanical instability and slight offsets in rotation and translation of the source, detector and/or the sample stage themselves from the measured parameters. Although, many studies have been dealing with the calibration problems for a specific X-ray CT system, most of those methods require specificallydesigned and/or expensive phantoms. In this work, we introduce a low-cost, easy-to-use and readily available phantom, built from LEGO bricks that serves as a structure to hold small, ‘metal’ beads for geometric calibration of a tomographic X-ray system.
... Third, the problem of limited angle tomography needs to be solved. To solve these issues, they used the calibration phantom developed by Cho et al. [23] for the geometric calibration of the device. Furthermore, the geometric errors originating from the non-repeatability of the C-arm trajectory were corrected using the information from the 3D scanner. ...
... This suggests that the geometrical calibration of internal parameters obtained with checkerboard calibration can be used for image reconstruction. As opposed to the calibration phantom in [23], the checkerboard pattern was easier to prepare, and off-the-shelf software is readily available for this kind of planar calibration. ...
In orthopedic surgeries, such as osteotomy and osteosynthesis, an intraoperative 3D reconstruction of the bone would enable surgeons to quickly assess the fracture reduction procedure with preoperative planning. Scanners equipped with such functionality are often more expensive than a conventional C-arm fluoroscopy device. Moreover, a C-arm fluoroscopy device is commonly available in many orthopedic facilities. Based on the widespread use of such equipment, this paper proposes a method to reconstruct the 3D structure of bone with a conventional C-arm fluoroscopy device. We focus on wrist bones as the target of reconstruction in this research as this will facilitate a flexible imaging scheme. Planar markers are attached to the target object and are tracked in the fluoroscopic image for C-arm pose estimation. The initial calibration of the device is conducted using a checkerboard pattern. In general, reconstruction algorithms are sensitive to geometric calibration errors. To assess the practicality of the method for reconstruction, a simulation study demonstrating the effect of checkerboard thickness and spherical marker size on reconstruction quality was conducted.
... Many methods can be found in the literature for estimating geometry parameters, that is, geometry calibration, in CT systems. However, most research is concentrated on the medical field, where a single source-detector pair rotating around the scanning object is considered [15][16][17]. In the CT scanner used in this study, the measurement setting has the opposite configuration: the source and detector are fixed, and the object is rotated while scanning to get projections at different angles. ...
... A calibration method for cone-beam geometry that employs a linear parameter estimation approach is proposed in [17]. The method uses a transparent cylindrical acrylic tube with 24 steel ball bearings as a calibration phantom, but the approach can be adapted also to other phantom configurations. ...
We consider geometry parameter estimation in industrial sawmill fan-beam X-ray tomography. In such industrial settings, scanners do not always allow identification of the location of the source-detector pair, which creates the issue of unknown geometry. This work considers two approaches for geometry estimation. Our first approach is a calibration object correlation method in which we calculate the maximum cross-correlation between a known-sized calibration object image and its filtered backprojection reconstruction and use differential evolution as an optimiser. The second approach is projection trajectory simulation, where we use a set of known intersection points and a sequential Monte Carlo method for estimating the posterior density of the parameters. We show numerically that a large set of parameters can be used for artefact-free reconstruction. We deploy Bayesian inversion with Cauchy priors for synthetic and real sawmill data for detection of knots with a very low number of measurements and uncertain measurement geometry.
... This method has been used in commercial systems such as Varian's IsoCal [13][14][15]. To correct the geometric uncertainty in rotation, Cho et al. proposed using an independent coordinate system combined with CBCT images [16]. Yang et al. designed a simpler model that is easier to obtain [17]. ...
Medical accelerators have been widely used in tumor radiation therapy. Accurate isocenter coincidence between treatment beams and imaging systems is critical for image-guided radiation therapy (IGRT). We propose a method utilizing a phantom with marker spheres to detect the Nine Degrees of Freedom (9-DOF) in the system’s geometric model to assess isocenter coincidence between the treatment beams and the kV cone-beam computed tomography (CBCT). The phantom was initially aligned with the accelerator. Subsequently, the projections of the treatment and CBCT beams’ were acquired separately with full gantry rotation. By analyzing the marker spheres’ position in both the treatment beam and CBCT beam projections, the 9-DOF parameters were calculated. A comparison with a Winston-Lutz-based system was performed. Then, the analysis revealed imprecise circular trajectories with noticeable random deviations in the rotations of both the treatment beams and CBCT. The isocenter deviations for the treatment beams and CBCT were 0.18 mm (X), −0.49 mm (Y), and −0.35 mm (Z) after trajectories fitting, respectively. The rotational planes of the two systems exhibited a pinch angle of 0.0235°. This proposed method offers a quantitative assessment of the geometric pose of the source and the detector panel, and the isocenter coincidence of the treatment beams and imaging systems of an accelerator at each gantry angle.
... In total, 13 scans ranging from -30 to 30 degrees in 5 degree steps are collected. From these scans, projection matrices are calculated following the method from Cho et al. [1]. For a new tilted acquisition, the device's tilt angle encoder is read out with 0.1 • precision and projection matrices are calculated from the neighboring calibration matrices via interpolation of C-Arm pose and imaging intrinsics like in [10]. ...
Purpose
Intraoperative cone-beam CT imaging enables 3D validation of implant positioning and fracture reduction for orthopedic and trauma surgeries. However, the emergence of metal artifacts, especially in the vicinity of metallic objects, severely degrades the clinical value of the imaging modality. In previous works, metal artifact avoidance (MAA) methods have been shown to reduce metal artifacts by adapting the scanning trajectory. Yet, these methods fail to translate to clinical practice due to remaining methodological constraints and missing workflow integration.
Methods
In this work, we propose a method to compute the spatial distribution and calibrated strengths of expected artifacts for a given tilted circular trajectory. By visualizing this as an overlay changing with the C-Arm’s tilt, we enable the clinician to interactively choose an optimal trajectory while factoring in the procedural context and clinical task. We then evaluate this method in a realistic human cadaver study and compare the achieved image quality to acquisitions optimized using global metrics.
Results
We assess the effectiveness of the compared methods by evaluation of image quality gradings of depicted pedicle screws. We find that both global metrics as well as the proposed visualization of artifact distribution enable a drastic improvement compared to standard non-tilted scans. Furthermore, the novel interactive visualization yields a significant improvement in subjective image quality compared to the state-of-the-art global metrics. Additionally we show that by formulating an imaging task, the proposed method allows to selectively optimize image quality and avoid artifacts in the region of interest.
Conclusion
We propose a method to spatially resolve predicted artifacts and provide a calibrated measure for artifact strength grading. This interactive MAA method proved practical and effective in reducing metal artifacts in the conducted cadaver study. We believe this study serves as a crucial step toward clinical application of an MAA system to improve image quality and enhance the clinical validation of implant placement.
... For cone beam x-ray CT systems, a common geometry calibration method is to analyse projection images obtained from a calibrated reference object consisting of a set of markers [2,3]: by measuring the positions and dimensions of the projected marker objects in the x-ray projection images, the projection * Author to whom any correspondence should be addressed. ...
A method is presented for fitting the projected centres of spheres in cone beam x-ray imaging. By using a suitable coordinate system, the method allows direct and exact calculation of the sphere centre without fitting the projection shape with an ellipse and correcting from the ellipse centre to the sphere centre. Advantages in numerical implementation result from the number of unknown variables being reduced compared to ellipse fits. Additionally, the orientation of the detector relative to the x-ray source can be obtained from fitting the shapes of projections of multiple spheres without knowledge of the positions or dimensions of the spheres. The accuracy of the method is compared to other techniques using simulated x-ray projections.
... The source-axis distance (SAD) was 743.74 mm (measured using translation stage encoders) and the axis-detector distance (ADD) was 411.16 mm (magnification of 1.55×); the scan range was 200 • . Geometric calibration was performed using the method of Cho et al. 42 In all experiments, the FPD was operated in 2 × 2 pixel-binning (0.388 × 0.388 mm 2 ) and the x-ray source focal spot was set to 0.8 mm (compared to 0.6 and 1 mm focal spots available on the Multitom Rax system). The anode-cathode axis of the source-that is, the direction of the heel effect-was in the axial plane of the CBCT scans, perpendicular to detector columns. ...
Background
Dual‐energy (DE) detection of bone marrow edema (BME) would be a valuable new diagnostic capability for the emerging orthopedic cone‐beam computed tomography (CBCT) systems. However, this imaging task is inherently challenging because of the narrow energy separation between water (edematous fluid) and fat (health yellow marrow), requiring precise artifact correction and dedicated material decomposition approaches.
Purpose
We investigate the feasibility of BME assessment using kV‐switching DE CBCT with a comprehensive CBCT artifact correction framework and a two‐stage projection‐ and image‐domain three‐material decomposition algorithm.
Methods
DE CBCT projections of quantitative BME phantoms (water containers 100–165 mm in size with inserts presenting various degrees of edema) and an animal cadaver model of BME were acquired on a CBCT test bench emulating the standard wrist imaging configuration of a Multitom Rax twin robotic x‐ray system. The slow kV‐switching scan protocol involved a 60 kV low energy (LE) beam and a 120 kV high energy (HE) beam switched every 0.5° over a 200° angular span. The DE CBCT data preprocessing and artifact correction framework consisted of (i) projection interpolation onto matched LE and HE projections views, (ii) lag and glare deconvolutions, and (iii) efficient Monte Carlo (MC)‐based scatter correction. Virtual non‐calcium (VNCa) images for BME detection were then generated by projection‐domain decomposition into an Aluminium (Al) and polyethylene basis set (to remove beam hardening) followed by three‐material image‐domain decomposition into water, Ca, and fat. Feasibility of BME detection was quantified in terms of VNCa image contrast and receiver operating characteristic (ROC) curves. Robustness to object size, position in the field of view (FOV) and beam collimation (varied 20–160 mm) was investigated.
Results
The MC‐based scatter correction delivered > 69% reduction of cupping artifacts for moderate to wide collimations (> 80 mm beam width), which was essential to achieve accurate DE material decomposition. In a forearm‐sized object, a 20% increase in water concentration (edema) of a trabecular bone‐mimicking mixture presented as ∼15 HU VNCa contrast using 80–160 mm beam collimations. The variability with respect to object position in the FOV was modest (< 15% coefficient of variation). The areas under the ROC curve were > 0.9. A femur‐sized object presented a somewhat more challenging task, resulting in increased sensitivity to object positioning at 160 mm collimation. In animal cadaver specimens, areas of VNCa enhancement consistent with BME were observed in DE CBCT images in regions of MRI‐confirmed edema.
Conclusion
Our results indicate that the proposed artifact correction and material decomposition pipeline can overcome the challenges of scatter and limited spectral separation to achieve relatively accurate and sensitive BME detection in DE CBCT. This study provides an important baseline for clinical translation of musculoskeletal DE CBCT to quantitative, point‐of‐care bone health assessment.
... A calibration method for cone-beam geometry that employs a calibration phantom to estimate the geometry parameters is proposed in [14]. The method uses a transparent cylindrical acrylic tube with 24 steel ball bearings as a calibration phantom, but the approach can be adapted also to other phantom configurations. ...
We consider geometry parameter estimation in industrial sawmill fan-beam X-ray tomography. In such industrial settings, scanners do not always allow identification of the location of the source–detector pair, which creates the issue of unknown geometry. This work considers an approach for geometry estimation based on the calibration object. We parametrise the geometry using a set of 5 parameters. To estimate the geometry parameters, we calculate the maximum cross-correlation between a known-sized calibration object image and its filtered backprojection reconstruction and use differential evolution as an optimiser. The approach allows estimating geometry parameters from full-angle measurements as well as from sparse measurements. We show numerically that different sets of parameters can be used for artefact-free reconstruction. We deploy Bayesian inversion with first-order isotropic Cauchy difference priors for reconstruction of synthetic and real sawmill data with a very low number of measurements.
... In essence, this correction is effective for all realizable source and detector angular positions and trajectories. The importance of this underlying approach, which is pivotal for achieving sharp, high-resolution 3D images, has been outlined in literature 15 and has been further refined for use with the ImagingRing-m in literature. 16 The geometrical accuracy achievable with this type of flexmap correction is, however, compromised in cases of focal spot (FS) displacement, which may occur when using different settings (FS size, tube current, tube potential) or when operating at thermal conditions different to those used during calibration (see Table 2). ...
Background
Misalignment or double‐contouring artifacts can appear in high‐resolution 3D cone beam computed tomography (CBCT) images, potentially indicating geometric accuracy issues in the projection data. Such artifacts may go unnoticed in low‐resolution images and could be associated with changes in the focal spot (FS) position.
Purpose
High‐resolution 3D‐CBCT imaging by a mobile imaging device with a large gantry clearance offers more versatility for clinical workflows in image‐guided brachytherapy (IGBT), intraoperative radiation therapy (IORT), and spinal, as well as maxillofacial surgery. However, misalignment or double‐contouring artifacts hinder workflow advancements in these domains. This paper introduces intrinsic calibration and geometrical correction methods as extensions to a well‐established technique for addressing geometrical deviations resulting from factors such as gravity or mechanical inconsistencies. These extensions cover shifts and drifts of the FS depending on FS size selection, temperature, tube current, and tube potential. The proposed methods effectively mitigate artifacts in high‐resolution CBCT images stemming from geometrical inaccuracies in projection data, without requiring additional equipment like a pinhole device.
Methods
Geometrical offsets and drifts of the x‐ray tube FS were characterized on a mobile multi‐purpose imaging system, the ImagingRing‐m. A pinhole‐like experiment was simulated by adjusting the movable collimation unit to a small rectangular aperture within the FS size range. The influence of filament selection, that is, FS size, temperature, the relatively low tube currents, as well as tube potential settings have been studied on two different monobloc types sharing the same x‐ray tube insert. The Catphan 504 and an Alderson head phantom were used to assess resulting image artifacts.
Results
Switching the FS size to one different from what was used for geometrical (gravitation, mechanical variations) calibration induced the most notable position changes of the x‐ray FS, resulting in double‐contouring artifacts and blurring of high‐resolution 3D‐CBCT images. Incorporating these shifts into a geometrical correction method effectively minimized these artifacts. Thermal drifts exhibited the second largest geometrical changes, comparable to FS size shifts across the thermal operating conditions of the x‐ray system. The proposed thermal drift compensation markedly reduced thermal drift effects. Tube current and potential had little impact within the range of available tube currents, eliminating the need for compensation in current applications.
Conclusions
Augmenting the geometrical calibration pipeline with proposed FS drift compensations yielded significant enhancements in image quality for high‐resolution reconstructions. While compensation for thermal effects posed challenges, it proved achievable. The roles of tube current and potential were found to be negligible.
... The camera pose describing the imaging geometry was determined through a process of calibration of the projective parameters, which was implemented following the well know Flexmap approach [31,32], extended to 9-DoF w.r.t. the system operating in Room #2 for higher accuracy [15]. This calibration method requires prior knowledge of a cloud of points embedded in a calibration phantom. ...
This paper describes the design, installation, and commissioning of an in-room imaging device developed at the Centro Nazionale di Adroterapia Oncologica (CNAO, Pavia, Italy). The system is an upgraded version of the one previously installed in 2014, and its design accounted for the experience gained in a decade of clinical practice of patient setup verification and correction through robotic-supported, off-isocenter in-room image guidance. The system's basic feature consists of image-based setup correction through 2D/3D and 3D/3D registration through a dedicated HW/SW platform. The major update with respect to the device already under clinical usage resides in the implementation of a functionality for extending the field of view of the reconstructed Cone Beam CT (CBCT) volume, along with improved overall safety and functional optimization. We report here details on the procedures implemented for system calibration under all imaging modalities and the results of the technical and preclinical commissioning of the device performed on two different phantoms. In the technical commissioning, specific attention was given to the assessment of the accuracy with which the six-degrees-of-freedom correction vector computed at the off-isocenter imaging position was propagated to the planned isocentric irradiation geometry. During the preclinical commissioning, the entire clinical-like procedure for detecting and correcting imposed, known setup deviation was tested on an anthropomorphic radioequivalent phantom. Results showed system performance within the sub-millimeter and sub-degree range according to project specifications under each imaging modality, making it ready for clinical application.
... Guidewire tip localization using backprojection The method for 3D guidewire localization uses the geometric model of the imaging system. Such models are commonly available in C-arms used for 3D CBCT imaging and are obtained through a geometric calibration process (Cho et al 2005) ahead of time. The geometry is represented as a set of projection matrices, P , q { } for each view (i.e. ...
Objective. Surgical guidewires are commonly used in placing fixation implants to stabilize fractures. Accurate positioning of these instruments is challenged by difficulties in 3D reckoning from 2D fluoroscopy. This work aims to enhance the accuracy and reduce exposure times by providing 3D navigation for guidewire placement from as little as two fluoroscopic images.
Approach. Our approach combines machine learning-based segmentation with the geometric model of the imager to determine the 3D poses of guidewires. Instrument tips are encoded as individual keypoints, and the segmentation masks are processed to estimate the trajectory. Correspondence between detections in multiple views is established using the pre-calibrated system geometry, and the corresponding features are backprojected to obtain the 3D pose. Guidewire 3D directions were computed using both an analytical and an optimization-based method. The complete approach was evaluated in cadaveric specimens with respect to potential confounding effects from the imaging geometry and radiographic scene clutter due to other instruments.
Main results. The detection network identified the guidewire tips within 2.2 mm and guidewire directions within 1.1°, in 2D detector coordinates. Feature correspondence rejected false detections, particularly in images with other instruments, to achieve 83% precision and 90% recall. Estimating the 3D direction via numerical optimization showed added robustness to guidewires aligned with the gantry rotation plane. Guidewire tips and directions were localized in 3D world coordinates with a median accuracy of 1.8 mm and 2.7°, respectively.
Significance. The paper reports a new method for automatic 2D detection and 3D localization of guidewires from pairs of fluoroscopic images. Localized guidewires can be virtually overlaid on the patient’s pre-operative 3D scan during the intervention. Accurate pose determination for multiple guidewires from two images offers to reduce radiation dose by minimizing the need for repeated imaging and provides quantitative feedback prior to implant placement.
... Such prerequisites are not satisfied in robotic CT because of its special structure hence these methods are not appropriate for this new system. There are also methods intended to offer geometry information of single angles [7][8][9]. Majority of these methods are based on well-designed calibration phantoms. The helical configuration phantom [10] is the most popular design among these phantoms, because it can avoid overlap of markers in almost all angles, which benefits extraction of markers. ...
Robotic computed tomography (CT) consists of two separate manipulators which carry the source and detector, respectively. Various errors occur in motion due to lack of rigid connection, which may change scanning trajectory of this system. Some methods aimed at recovering geometry relation have occurred. However, these methods are relied on circular scanning trajectory. Projection matrix is the matrix form of geometry definition, which contains geometric parameters in the matrix and transforms geometry calculation into homogeneous matrix calculation. It is suitable for robotic CT because of its irrelevance between angles. Besides, iteration reconstruction algorithm makes no assumptions on scanning trajectories, which is suitable for arbitrary scanning trajectories. Hence, this study combines iteration reconstruction algorithm with the concept of projection matrix to fill the gap. In this study, we established a transformation between projection matrix and ray function, and construct corresponding projection model. Projection matrix based iterative reconstruction algorithm was then developed and validated by simulation and experiment. Uncooperative rotation of manipulators, jitter in motion and non-circular motion trajectories were simulated. FDK, projection matrix-based FDK and projection matrix-based iterative method were compared. Real experiments were also conducted. The results showed projection matrix based iterative reconstruction could lead to better image quality against motion error. In summary, this study provided a high-precision reconstruction approach for robotic CT.
... Phân tích 7 phim CBCT/ BN của 40 BN, 280 phim với bốn vị trí clipbox khác nhau (tổng số 1120 phim). Việc hiệu chỉnh tâm điều trị CBCT đến tâm máy gia tốc được thực hiện trước khi bắt đầu nghiên cứu theo khuyến cáo hiện hành [3]. Đồng thuận chấp nhận nếu sai số nhỏ hơn 3mm theo mọi hướng. ...
Mục tiêu: Đánh giá hiệu quả điều trị dựa trên phương pháp trùng khớp hình ảnh thay đổi giải phẫu của hệ thống kiểm soát sai số ConeBeam CT (CBCT): chụp cắt lớp hình nón (sử dụng phần mềm tái tạo ảnh thuật toán thể tích số theo không gian ba chiều - 3D) điều trị ung thư thực quản 1/3 trên. Phương pháp: 40 bệnh nhân ung thư thực quản 1/3 trên chụp CBCT xác định bốn thể tích: bia kế hoạch (PTV), cựa khí quản, cột sống, lồng ngực. Thiết lập vị trí thể tích PTV được so sánh và hiệu chỉnh dựa trên cựa khí quản, cột sống và lồng ngực (Clipbox-PTV (C-PTV), Clipbox-cựa khí quản (C-cựa khí quản), Clipbox-cột sống (C-cột sống), Clipbox-lồng ngực (C-lồng ngực). Kết quả: 1120 phim chụp conebeam CT đã được thực hiện. Hiệu chỉnh giữa C-PTV và C-lồng ngực có thiết lập vị trí tương đồng cao nhất theo chiều trên/dưới; phải/trái; trước/sau với tỷ lệ lần lượt là 60.7%; 88.7% và 82%. Chụp conebeam CT so sánh sai số di động sử dụng C-cột sống có tỷ lệ cao nhất trên các phim chụp. Đáp ứng hoàn toàn chiếm 70%, đáp ứng một phần 30%. Kết luận: Hiệu chỉnh sai số do di lệch khi thiết lập tư thế bệnh nhân dựa trên CBCT cho thấy nhiều thay đổi giải phẫu mà lâm sàng không phát hiện ra. Việc xác định chính xác thể tích xạ trị rất quan trọng trong điều trị đạt hiệu quả cao UTTQ.
... already calibrated computer tomography machines. Further, one can distinguish whether requirements are made to the number of spheres of which the calibration body consists of or their spatial distribution [7,[14][15][16][17][18][19][20][21]. ...
Conventional industrial X-Ray CT systems are limited in their movement because of their limited degrees of freedom and overall design. Equipping CT with two industrial robotic arms, e.g. for manipulating source and detector, overcomes this limitation. Industrial robots are less restricted in the positioning and orientation of their X-ray tools than comparable industrial CT systems, making them flexible manipulators. However, their absolute positioning accuracy is usually below the minimum requirement for use in computed tomography. This paper proposes a calibration method with a variable, low-cost calibration body that allows pose correction of arbitrary projection geometries. The results from a twin robotic CT system will be evaluated via simulated projection data and actual experimental computer tomographic reconstruction.
... Many research groups have explored the phantom-base methods, in which the calibration procedure must be performed before imaging tasks, using a phantom with known geometric information. Some of the phantom-base methods adopt dedicated phantoms consisting of many markers with special patterns [1] [2] to acquire all geometric parameters. In such methods, ample markers and precise determination of markers' position are crucial for accurate geometric calibration [3]. ...
In this paper, we intend to provide a method for calibration of geometric CBCT systems without the need for phantom and prior knowledge related to the object which is normally used in 2D-3D registration methods for geometrical calibration. To this end, we use an iterative algorithm based on comparison between measured data and DRRs1 which are obtained from reconstructed images with different geometries to find geometrical parameters of the system. Our proposed method shows strong agreement with phantom based methods.
... A residual network was employed to learn the bead position in the projection data, minimize the experimental projection bead and the simulated projection interbead distance, derive the error parameters, and realize the calibration. Cho et al. [21] and Chetley et al. [22] proposed another model that used two spherical steel loops placed on an acrylic cylinder for calibration. Such low-cost, simple, and flexible self-calibration methods are well suited to the requirements of a portable CBCT system. ...
In outdoor environments or environments with space restrictions, it is difficult to transport and use conventional computed tomography (CT) systems. Therefore, there is an urgent need for rapid reconstruction of portable cone-beam CT (CBCT) systems. However, owing to its portability and the characteristics of temporary construction environments, high precision spatial location is difficult to achieve with portable CBCT systems. To overcome these limitations, we propose an iterative self-calibration improvement method with a self-calculated initial value based on the projection relationship and image features. The CT value of an open field image was used as the weight value of the projection data in the subsequent experiments to reduce the nonlinear attenuation of the projection intensity. Subsequently, an initial value was obtained based on the invariance of the rotation axis. Finally, self-calibration was realized iteratively using the reconstructed image. This method overcomes the main problem of the rotation axis invariance calibration algorithm—high similarity between the adjacent positions of symmetrical homogeneous materials. The proposed method not only improves the precision of self-calibration based on the projection relationship, but also reduces the performance cost and solution time of the self-calibration algorithm based on the image features. Thus, it satisfies the precision requirements for self-calibration of portable CBCT systems.
... A transparent plastic cylinder with a total of 24 steel ball bearings equally located in two circles at the cylinder's top and bottom were used to calculate the ellipses parameters and thus detector plane shift, angular error as well as X-ray source distance were deduced. [13] A deep learning approach with a phantom composed of plastic Lego bricks was proposed by Nguyen et al.. Five metal ball bearings were placed inside a bar-shaped Lego phantom. The ball bearings were placed in a way not to overlap each other when being Xrayed. ...
... P where x p is the true location of a target in the 2D projection, q P is the projection matrix associated with gantry angle q [determined by geometric calibration of C-arm (Cho et al 2005)], T ROI is the computed 3D-2D transform, and x 3D is the location of the target in the 3D volume. Definition of x p and x 3D was performed by manually selecting the pixel or voxel (respectively) determined to be in the center of the target. ...
Purpose:
Target localization in pulmonary interventions (e.g., transbronchial biopsy of a lung nodule) is challenged by deformable motion and may benefit from fluoroscopic overlay of the target to provide accurate guidance. We present and evaluate a 3D-2D image registration method for fluoroscopic overlay in the presence of tissue deformation using a multi-resolution / multi-scale (MRMS) framework with an objective function that drives registration primarily by soft-tissue image gradients.
Methods:
The MRMS method registers 3D cone-beam CT to 2D fluoroscopy without gating of respiratory phase by coarse-to-fine resampling and global-to-local rescaling about target regions-of-interest (ROIs). A variation of the gradient orientation (GO) similarity metric (denoted GO') was developed to downweight bone gradients and drive registration via soft-tissue gradients. Performance was evaluated in terms of projection distance error at isocenter (PDEiso). Phantom studies determined nominal algorithm parameters and capture range. Preclinical studies used a freshly deceased, ventilated porcine specimen to evaluate performance in the presence of real tissue deformation and a broad range of 3D-2D image mismatch.
Results:
Nominal algorithm parameters were identified that provided robust performance over a broad range of motion (0-20 mm), including an adaptive parameter selection technique to accommodate unknown mismatch in respiratory phase. The GO' metric yielded median PDEiso = 1.2 mm, compared to 6.2 mm for conventional GO. Preclinical studies with real lung deformation demonstrated median PDEiso = 1.3 mm with MRMS + GO' registration, compared to 2.2 mm with a conventional transform. Runtime was 26 s and can be reduced to 2.5 s given a prior registration within ~5 mm as initialization.
Conclusions:
MRMS registration via soft-tissue gradients achieved accurate fluoroscopic overlay in the presence of deformable lung motion. By driving registration via soft-tissue image gradients, the method avoided false local minima presented by bones and was robust to a wide range of motion magnitude.
... The projections of the balls form an ellipse from which the calibration parameters can be estimated. [3][4][5] Many computer vision methods are based on a pinhole camera model. The model relates a 3D point (X, Y, Z) lying in the scene to a 2D point (u, v) on the detector. ...
... However, it is usually difficult to achieve the ideal spatial resolution with nano-CT because the drift of the focal spot (emission point) inside the X-ray source, thermal expansion of the trestle, and object motion during long-term scanning can contribute to projection drift [2][3][4][5]. Consequently, the reconstruction results contain serious drift artifacts [6][7][8] such as resolution degradation [9,10]. Therefore, it is necessary to correct the drift artifacts [11,12]. ...
A self-correction method for the drift artifacts of laboratory cone-beam nanoscale X-ray computed tomography (nano-CT) based on the trajectory of projection centroid (TPC) is proposed. This method does not require additional correction phantoms, simplifying the correction process. The whole TPC is estimated by the partial TPC in the optimal projection set. The projection drift is calculated by the measured TPC and the estimated TPC. The interval search method is used so that the proposed method can adapt to the case of a truncated projection due to drift. The fixed-angle scanning experiment of the Siemens star and the partial derivative analysis of the projection position show the necessity of correcting drift artifacts. Further, the Shepp–Logan phantoms with different drift levels are simulated. The results show that the proposed method can effectively estimate the horizontal and vertical drifts within the projection drift range of ±2 mm (27 pixels) with high accuracy. Experiments were conducted on tomato seed and bamboo stick to validate the feasibility of the proposed method for samples with different textures. The correction effect on different reconstructed slices indicates that the proposed method provides performance superior to the reference scanning method (RSM) and global fitting. In addition, the proposed method requires no extra scanning, which improves the acquisition efficiency, as well as radiation utilization.
... The algorithm makes use of a calibration phantom consisting of 24 steel ball bearings in a known geometry. The method estimates geometric parameters including the position of the X-ray source, and rotation center of the detector, and gantry angle, and can describe complex source-detector trajectories [8]. Li et al. ...
Computer Tomography (CT) is a complicated imaging system, requiring highly geometric positioning. We found a special artifact caused by detection plane tilted around z-axis. In short scan cone-beam reconstruction, this kind of geometric deviation result in half circle shaped fuzzy around highlighted particles in reconstructed slices. This artifact is distinct near the slice periphery, but deficient around the slice center. We generated mathematical models, and InceptionV3-R deep network to study the slice artifact features to estimate the detector z-axis tilt angle. The testing results are: mean absolute error of 0.08819 degree, the Root mean square error of 0.15221 degree and R-square of 0.99944. A geometric deviation recover formula was deduced, which can eliminate this artifact efficiently. This research enlarges the CT artifact knowledge hierarchy, and verifies the capability of machine learning in CT geometric deviation artifact recoveries.
... Defective pixels were corrected with median-filtering based on the nearest, non-defective neighbors prior to subsequent image processing. Geometric calibration was performed using the two-circle BB phantom and analytical solution described by Cho et al. 28 Bare beam (I 0 ) normalization was estimated as the mean signal in flat-field images. For technique settings that would saturate the detector in the bare-beam, I 0 was linearly extrapolated from values measured in the (sub-saturation) linear operating range of the detector. ...
Background
Indirect detection flat‐panel detectors (FPDs) consisting of hydrogenated amorphous silicon (a‐Si:H) thin‐film transistors (TFTs) are a prevalent technology for digital x‐ray imaging. However, their performance is challenged in applications requiring low exposure levels, high spatial resolution, and high frame rate. Emerging FPD designs using metal oxide TFTs may offer potential performance improvements compared to FPDs based on a‐Si:H TFTs.
Purpose
This work investigates the imaging performance of a new indium gallium zinc oxide (IGZO) TFT‐based detector in 2D fluoroscopy and 3D cone‐beam CT (CBCT).
Methods
The new FPD consists of a sensor array combining IGZO TFTs with a‐Si:H photodiodes and a 0.7‐mm thick CsI:Tl scintillator. The FPD was implemented on an x‐ray imaging bench with system geometry emulating intraoperative CBCT. A conventional FPD with a‐Si:H TFTs and a 0.6‐mm thick CsI:Tl scintillator was similarly implemented as a basis of comparison. 2D imaging performance was characterized in terms of electronic noise, sensitivity, linearity, lag, spatial resolution (modulation transfer function, MTF), image noise (noise‐power spectrum, NPS), and detective quantum efficiency (DQE) with entrance air kerma (EAK) ranging from 0.3 to 1.2 μGy. 3D imaging performance was evaluated in terms of the 3D MTF and noise‐equivalent quanta (NEQ), soft‐tissue contrast‐to‐noise ratio (CNR), and image quality evident in anthropomorphic phantoms for a range of anatomical sites and dose, with weighted air kerma, Kw${K_w}$, ranging from 0.8 to 4.9 mGy.
Results
The 2D imaging performance of the IGZO‐based FPD exhibited up to ∼1.7× lower electronic noise than the a‐Si:H FPD at matched pixel pitch. Furthermore, the IGZO FPD exhibited ∼27% increase in mid‐frequency DQE (1 mm⁻¹) at matched pixel size and dose (EAK ≈ 1.0 μGy) and ∼11% increase after adjusting for differences in scintillator thickness. 2D spatial resolution was limited by the scintillator for each FPD. The IGZO‐based FPD demonstrated improved 3D NEQ at all spatial frequencies in both head (≥25% increase for all dose levels) and body (≥10% increase for Kw${K_w}$ ≤2 mGy) imaging scenarios. These characteristics translated to improved low‐contrast visualization in anthropomorphic phantoms, demonstrating ≥10% improvement in CNR and extension of the low‐dose range for which the detector is input‐quantum limited.
Conclusion
The IGZO‐based FPD demonstrated improvements in electronic noise, image lag, and NEQ that translated to measurable improvements in 2D and 3D imaging performance compared to a conventional FPD based on a‐Si:H TFTs. The improvements are most beneficial for 2D or 3D imaging scenarios involving low‐dose and/or high‐frame rate.
... The error model of medical XCT systems with both the detector and source rotating considered 9 parameters. The calibration used a calibrated reference sample consisting of 24 steel ball bearings embedded in a cylindrical plastic phantom, where the position of these balls are well established [227]. The calibration relies on projection images, and approximately 300 images were used to calibrate the whole system. ...
Advanced manufacturing technologies, led by additive manufacturing, have undergone significant growth in recent years. These technologies enable engineers to design parts with reduced weight while maintaining structural and functional integrity. In particular, metal additive manufacturing parts are increasingly used in application areas such as aerospace, where a failure of a mission-critical part can have dire safety consequences. Therefore, the quality of these components is extremely important. A critical aspect of quality control is dimensional evaluation, where measurements provide quantitative results that are traceable to the standard unit of length, the metre. Dimensional measurements allow designers, manufacturers and users to check product conformity against engineering drawings and enable the same quality standard to be used across the supply chain nationally and internationally. However, there is a lack of development of measurement techniques that provide non-destructive dimensional measurements beyond common non-destructive evaluation focused on defect detection. X-ray computed tomography (XCT) technology has great potential to be used as a non-destructive dimensional evaluation technology. However, technology development is behind the demand and growth for advanced manufactured parts. Both the size and the value of advanced manufactured parts have grown significantly in recent years, leading to new requirements of dimensional measurement technologies. This paper is a cross-disciplinary review of state-of-the-art non-destructive dimensional measuring techniques relevant to advanced manufacturing of metallic parts at larger length scales, especially the use of high energy XCT with source energy of greater than 400 kV to address the need in measuring large advanced manufactured parts. Technologies considered as potential high energy x-ray generators include both conventional x-ray tubes, linear accelerators, and alternative technologies such as inverse Compton scattering sources, synchrotron sources and laser-driven plasma sources. Their technology advances and challenges are elaborated on. The paper also outlines the development of XCT for dimensional metrology and future needs.
Background
Accurate tomographic reconstructions require the knowledge of the actual acquisition geometry. Many mobile C‐arm CT scanners have poorly reproducible acquisition geometries and thus need acquisition‐specific calibration procedures. Most of geometric self‐calibration methods based on projection data either need prior information or are limited to the estimation of a low number of geometric calibration parameters. Other self‐calibration methods generally use a calibration pattern with known geometry and are hardly implementable in practice for clinical applications.
Purpose
We present a three‐step marker based self‐calibration method which does not require the prior knowledge of the calibration pattern and thus enables the use of calibration patterns with arbitrary markers positions.
Methods
The first step of the method aims at detecting the set of markers of the calibration pattern in each projection of the CT scan and is performed using the YOLO (You Only Look Once) Convolutional Neural Network. The projected marker trajectories are then estimated by a sequential projection‐wise marker association scheme based on the Linear Assignment Problem which uses Kalman filters to predict the markers 2D positions in the projections. The acquisition geometry is finally estimated from the marker trajectories using the Bundle‐adjustment algorithm.
Results
The calibration method has been tested on realistic simulated images of the ICRP (International Commission on Radiological Protection) phantom, using calibration patterns with 10 and 20 markers. The backprojection error was used to evaluate the self‐calibration method and exhibited sub‐millimeter errors. Real images of two human knees with 10 and 30 markers calibration patterns were then used to perform a qualitative evaluation of the method, which showed a remarkable artifacts reduction and bone structures visibility improvement.
Conclusions
The proposed calibration method gave promising results that pave the way to patient‐specific geometric self‐calibrations in clinics.
Purpose
A fundamental parameter to evaluate the beam delivery precision and stability on a clinical linear accelerator (linac) is the focal spot position (FSP) measured relative to the collimator axis of the radiation head. The aims of this work were to evaluate comprehensive data on FSP acquired on linacs in clinical use and to establish the ability of alternative phantoms to detect effects on patient plan delivery related to FSP.
Methods
FSP measurements were conducted using a rigid phantom holding two ball-bearings at two different distances from the radiation source. Images of these ball-bearings were acquired using the electronic portal imaging device (EPID) integrated with each linac. Machine QA was assessed using a radiation head-mounted PTW STARCHECK phantom. Patient plan QA was investigated using the SNC ArcCHECK phantom positioned on the treatment couch, irradiated with VMAT plans across a complete 360° gantry rotation and three X-ray energies.
Results
This study covered eight Elekta linacs, including those with 6 MV, 18 MV, and 6 MV flattening-filter-free (FFF) beams. The largest range in the FSP was found for 6 MV FFF. The FSP of one linac, retrofitted with 6 MV FFF, displayed substantial differences in FSP compared to 6 MV FFF beams on other linacs, which all had FSP ranges less than 0.50 mm and 0.25 mm in the lateral and longitudinal directions, respectively. The PTW STARCHECK phantom proved effective in characterising the FSP, while the SNC ArcCHECK measurements could not discern FSP-related features.
Conclusions
Minor variations in FSP may be attributed to adjustments in linac parameters, component replacements necessary for beam delivery, and the wear and tear of various linac components, including the magnetron and gun filament. Consideration should be given to the ability of any particular phantom to detect a subsequent impact on the accuracy of patient plan delivery.
Background:
Geometric calibration is essential in developing a reliable computed tomography (CT) system. It involves estimating the geometry under which the angular projections are acquired. Geometric calibration of cone beam CTs employing small area detectors, such as currently available photon counting detectors (PCDs), is challenging when using traditional-based methods due to detectors' limited areas.
Objective:
This study presented an empirical method for the geometric calibration of small area PCD-based cone beam CT systems.
Methods:
Unlike the traditional methods, we developed an iterative optimization procedure to determine geometric parameters using the reconstructed images of small metal ball bearings (BBs) embedded in a custom-built phantom. An objective function incorporating the sphericities and symmetries of the embedded BBs was defined to assess performance of the reconstruction algorithm with the given initial estimated set of geometric parameters. The optimal parameter values were those which minimized the objective function. The TIGRE toolbox was employed for fast tomographic reconstruction. To evaluate the proposed method, computer simulations were carried out using various numbers of spheres placed in various locations. Furthermore, efficacy of the method was experimentally assessed using a custom-made benchtop PCD-based cone beam CT.
Results:
Computer simulations validated the accuracy and reproducibility of the proposed method. The precise estimation of the geometric parameters of the benchtop revealed high-quality imaging in CT reconstruction of a breast phantom. Within the phantom, the cylindrical holes, fibers, and speck groups were imaged in high fidelity. The CNR analysis further revealed the quantitative improvements of the reconstruction performed with the estimated parameters using the proposed method.
Conclusion:
Apart from the computational cost, we concluded that the method was easy to implement and robust.
Purpose:
Motivated by emerging cone-beam computed tomography (CBCT) systems and scan orbits, we aim to quantitatively assess the completeness of data for 3D image reconstruction-in turn, related to "cone-beam artifacts." Fundamental principles of cone-beam sampling incompleteness are considered with respect to an analytical figure-of-merit [FOM, denoted tan(ψmin)] and related to an empirical FOM (denoted zmod) for measurement of cone-beam artifact magnitude in a test phantom.
Approach:
A previously proposed analytical FOM [tan(ψmin), defined as the minimum angle between a point in the 3D image reconstruction and the x-ray source over the scan orbit] was analyzed for a variety of CBCT geometries. A physical test phantom was configured with parallel disk pairs (perpendicular to the z-axis) at various locations throughout the field of view, quantifying cone-beam artifact magnitude in terms of zmod (the relative signal modulation between the disks). Two CBCT systems were considered: an interventional C-arm (Cios Spin 3D; Siemens Healthineers, Forcheim Germany) and a musculoskeletal extremity scanner; Onsight3D, Carestream Health, Rochester, United States)]. Simulations and physical experiments were conducted for various source-detector orbits: (a) a conventional 360 deg circular orbit, (b) tilted and untilted semi-circular (196 deg) orbits, (c) multi-source (three x-ray sources distributed along the z axis) semi-circular orbits, and (d) a non-circular (sine-on-sphere, SoS) orbit. The incompleteness of sampling [tan(ψmin)] and magnitude of cone-beam artifacts (zmod) were evaluated for each system and orbit.
Results:
The results show visually and quantitatively the effect of system geometry and scan orbit on cone-beam sampling effects, demonstrating the relationship between analytical tan(ψmin) and empirical zmod. Advanced source-detector orbits (e.g., three-source and SoS orbits) exhibited superior sampling completeness as quantified by both the analytical and the empirical FOMs. The test phantom and zmod metric were sensitive to variations in CBCT system geometry and scan orbit and provided a surrogate measure of underlying sampling completeness.
Conclusion:
For a given system geometry and source-detector orbit, cone-beam sampling completeness can be quantified analytically (in terms arising from Tuy's condition) and/or empirically (using a test phantom for quantification of cone-beam artifacts). Such analysis provides theoretical and practical insight on sampling effects and the completeness of data for emerging CBCT systems and scan trajectories.
The 2D projection space-based motion compensation reconstruction (2D-MCR) is a kind of representative method for 3D reconstruction of rotational coronary angiography owing to its high efficiency. However, due to the lack of accurate motion estimation of the overlapping projection pixels, existing 2D-MCR methods may still have a certain level of under-sampling artifacts or lose accuracy for cases with strong cardiac motion. To overcome this, in this study, we proposed a motion estimation approach based on projective information disentanglement (PID-ME) for 3D reconstruction of rotational coronary angiography. The reconstruction method adopts the framework of 2D-MCR, which is referred to as 2D-PID-MCR. The PID-ME consists of two parts: generation of the reference projection sequence based on the fast simplified distance driven projector (FSDDP) algorithm, motion estimation and correction based on the projective average minimal distance measure (PAMD) model. The FSDDP algorithm generates the reference projection sequence faster and accelerates the whole reconstruction greatly. The PAMD model can disentangle the projection information effectively and estimate the motion of both overlapping and non-overlapping projection pixels accurately. The main contribution of this study is the construction of 2D-PID-MCR to overcome the inherent limitations of the existing 2D-MCR method. Simulated and clinical experiments show that the PID-ME, consisting of FSDDP and PAMD, can estimate the motion of the projection sequence data accurately and efficiently. Our 2D-PID-MCR method outperforms the state-of-the-art approaches in terms of accuracy and real-time performance.
In this work, we propose a robust offline geometry calibration method for an offset-detector-based dental cone-beam computed tomography (CBCT) system. Although a host of geometric calibration methods for CT system have been developed, the calibration of dental CBCT systems remains to be one of the challenging cases due to the presence of an offset detector and due to the smaller system dimensions. We highlight the technical difficulties encountered in such dental CBCT geometric calibration, and provide an efficient and robust recipe for the accurate calibration. Through a particular design of the phantom, a heuristic estimation of the isocenter, and an enforcement of smooth change of the extracted geometric parameters, we show that the aforementioned challenges can be overcome. Fabrication errors that may exist in the geometry calibration phantom are also considered. We scanned two physical phantoms with a commercial dental CBCT for evaluating the proposed geometry calibration method. The results confirm that the proposed method can achieve an accurate and efficient geometry calibration in the offset-detector-based CBCT systems.
In a linear tomosynthesis scanner designed for imaging histologic samples of several centimeters size at 10 µm resolution, the mechanical instability of the scanning stage (±10 µm) exceeded the resolution of the image system, making it necessary to determine the trajectory of the stage for each scan to avoid blurring and artifacts in the images that would arise from the errors in the geometric information used in 3D reconstruction. We present a method for online calibration by attaching a layer of randomly dispersed micro glass beads or calcium particles to the bottom of the sample stage. The method was based on a parametric representation of the rigid body motion of the sample stage-marker layer assembly. The marker layer was easy to produce and proven effective in the calibration procedure.
A hybrid imaging system consisting of a standard computed tomography (CT) scanner and a low-profile photon-counting detector insert in contact with the patient’s body has been used to produce ultrahigh-resolution images in a limited volume in chest scans of patients. The detector insert is placed on the patient bed as needed and not attached. Thus, its position and orientation in the scanner is dependent on the patient’s position and scan settings. To allow accurate image reconstruction, we devised a method of determining the relative geometry of the detector insert and the CT scanner for each scan using fiducial markers. This method uses an iterative registration algorithm to align the markers in the reconstructed volume from the detector insert to that of the concurrent CT scan. After obtaining precise geometric information of the detector insert relative to the CT scanner, the two complementary sets of images are summed together to create a detailed image with reduced artifacts.
In a linear tomosynthesis scanner designed for imaging histologic samples of several centimeter size at 10 micrometer resolution, the mechanical instability of the scanning stage (+/-10 micrometers) exceeded the resolution of the image system, making it necessary to determine the trajectory of the stage for each scan to avoid blurring and artifacts in the images that would arise from the errors in the geometric information used in 3D reconstruction. We present a method for online calibration by attaching a layer of randomly dispersed micro glass beads or calcium particles to the bottom of the sample stage. The marker layer was easy to produce and proven effective in the calibration procedure.
A hybrid imaging system consisting of a standard CT scanner and a low-profile photon-counting detector insert in contact with the patient's body has been used to produce ultrahigh-resolution images in a limited volume in chest scans of patients. The detector insert is placed on the patient bed as needed and not attached. Thus, its position and orientation in the scanner is dependent on the patient's position and scan settings. To allow accurate image reconstruction, we devised a method of determining the relative geometry of the detector insert and the CT scanner for each scan using fiducial markers. This method uses an iterative registration algorithm to align the markers in the reconstructed volume from the detector insert to that of the concurrent CT scan. After obtaining precise geometric information of the detector insert relative to the CT scanner, the two complementary sets of images are summed together to create a detailed image with reduced artifacts.
X-ray computed tomography (XCT) is increasingly used for quality control and non-destructive inspection in the manufacturing industry. Compared to conventional XCT machines, twin robot CT systems are a promising platform for the scanning of oversized workpieces without disassembling them. This work proposes a reference-free geometry estimation method based solely on X-ray images of the specimen to compensate for the positioning and orientation errors of the X-ray the imaging system (i.e. X-ray source and detector). The identification of the system misalignment is based on the Grangeat-based consistency conditions, and is further optimized by a searching based method. We theoretically demonstrates that it is possible to recover the geometric parameters of a twin robot CT system based on solely the X-ray images of a rigid object. Simulated and real X-ray scans are used to evaluate the proposed method both qualitatively in terms of reduction of artifacts in the reconstructed volume and quantitatively in terms of the accuracy of the calculated geometric parameters. Several optimizers are compared, and the proposed method significantly outperforms the others.
Recently there has been increasing interest in obtaining three-dimensional reconstructions of arterial vessels from multiple planar radiographs (obtained at angles around the object). Interventional angiography is the motivating application behind this research. Different methods have been proposed to acquire the planar data such as a gantry mounted x-ray image intensifier (XRII) or a C-arm mounted XRII. In order to obtain a three-dimensional reconstruction from a C-arm mounted XRII the trajectory of the source and detector system must be characterized. We have designed a calibration system that provides the necessary trajectory information using uniquely identifiable markers positioned on a cylinder. This calibration ring is to be placed around the patient's head, and consists of steel balls positioned in a predefined arrangement on a cylindrical acrylic support. The balls are arranged such that calibration can be done from almost any partial view, allowing reconstruction of a region of interest (ROI). Steel balls are placed around an acrylic cylinder, restricted to a band approximately 8.5 mm wide, thereby obscuring only a small fraction of the image. In this case the radiograph includes the region of interest (ROI) as well as a partial view of the calibration ring. This enables us to recover the geometry of X-ray imaging system from each individual frame. We call this process 'dynamic calibration' as opposed to 'off-line' calibration procedures which try to characterize the motion of C-arm before introducing the patient.
In cone-beam tomography, relatively small misalignment of the imaging system is geometrically magnified and may cause severe distortion of the reconstructed image. We describe a method for alignment of a cone-beam tomography system built on an x-ray microfocus tube, an image intensifier, and a high-resolution CCD camera. To obtain geometrical parameters of system misalignment, we suggest measuring two 180-deg- opposed cone-beam radiographs of a specially manufactured calibration aperture. An advantage of the aperture over other calibration objects is that we can easily restore its idealized picture by applying a certain threshold to the measured data. The method permits the lateral displacement vector and lateral tilt angle to be accurately found. Unlike other alignment methods, our approach enables virtual system alignment by using mathematical processing of the measured data, rather than moving the parts of the system. The virtually aligned system data are used for 3D image reconstruction by a standard filtered backprojection algorithm. Experimental results demonstrate considerable improvement of the image quality after applying the alignment method suggested.
Tomographic image quality depends on precisely determining the geometric parameters that reference the detector system to the transaxial imaging coordinate system. In addition to the projection of the centre of rotation onto the detector, fan beam geometry requires two other parameters that include the focal length and the projection of the focal point onto the detector. Heretofore no method has been developed for estimating the geometrical parameters of a fan beam detector system. A method is presented for estimating these parameters from centroids of the measured projections of a point source using the non-linear estimation algorithm due to Marquardt. The technique is applied to single photon emission computed tomography (SPECT) data from a rotating gamma camera using a fan beam collimator. The parameters can be determined very quickly in a clinical environment. The corresponding reconstructed images do not show image artefacts or loss of resolution characteristic of inaccurately determined geometric parameters.
3D reconstruction of arterial vessels from planar radiographs obtained at several angles around the object has gained increasing interest. The motivating application has been interventional angiography. In order to obtain a three-dimensional reconstruction from a C-arm mounted X-Ray Image Intensifier (XRII) traditionally the trajectory of the source and the detector system is characterized and the pixel size is estimated. The main use of the imaging geometry characterization is to provide a correct 3D-2D mapping between the 3D voxels to be reconstructed and the 2D pixels on the radiographic images.
We propose using projection matrices directly in a voxel driven backprojection for the reconstruction as opposed to that of computing all the geometrical parameters, including the imaging parameters. We discuss the simplicity of the entire calibration-reconstruction process, and the fact that it makes the computation of the pixel size, source to detector distance, and other explicit imaging parameters unnecessary.
A usual step in the reconstruction is sinogram weighting, in which the projections containing corresponding data from opposing directions have to be weighted before they are filtered and backprojected into the object space. The rotation angle of the C-arm is used in the sinogram weighting. This means that the C-arm motion parameters must be computed from projection matrices. The numerical instability associated with the decomposition of the projection matrices into intrinsic and extrinsic parameters is discussed in the context. The paper then describes our method of computing motion parameters without matrix decomposition. Examples of the calibration results and the associated volume reconstruction are also shown.
A filtered backprojection (FBP) algorithm is derived based on Feldkamp’s FBP algorithm for a cone beam geometry that has a displaced center of rotation. In cone beam single photon emission computed tomography (CB‐SPECT) the center of rotation displacement can degrade the reconstructed images. The center of rotation displacement of interest is mechanical shift, which is the displacement of the midplane of the cone beam collimator off the rotation center. Mechanical shift is characterized by two orthogonal components: the shift of the midplane of the cone beam collimator along the direction of the axis of rotation, and the distance between the midline of the cone beam collimator and the axis of rotation. This new algorithm corrects mechanical shift directly by incorporating mechanical shift into the algorithm. This new algorithm is evaluated using both Monte Carlo simulated data and experimentally acquired data. The results demonstrate that this algorithm is able to correct for blurring and the ‘‘doughnut’’ type artifacts caused by system mechanical shift and improve the image resolution.
An earlier paper [Simpson e t a l., Med. Phys. 9, 574 (1982)] described a computed tomographyCT scanner that was constructed by adding a detector array to a 4‐MV isocentric linear accelerator. Since the previous article, the detector array has been improved and we now demonstrate better than 3‐mm spatial resolution and better than 1% relative electron density discrimination. A series of pictures from volunteer patients is included. Normal anatomy is visualized with bone, muscle, fat, and air being clearly delineated.
The use of flat-panel imagers for cone-beam CT signals the emergence of an attractive technology for volumetric imaging. Recent investigations demonstrate volume images with high spatial resolution and soft-tissue visibility and point to a number of logistical characteristics (e.g., open geometry, volume acquisition in a single rotation about the patient, and separation of the imaging and patient support structures) that are attractive to a broad spectrum of applications. Considering application to image-guided (IG) procedures - specifically IG therapies - this paper examines the performance of flat-panel cone-beam CT in relation to numerous constraints and requirements, including time (i.e., speed of image acquisition), dose, and field-of-view. The imaging and guidance performance of a prototype flat panel cone-beam CT system is investigated through the construction of procedure-specific tasks that test the influence of image artifacts (e.g., x-ray scatter and beam-hardening) and volumetric imaging performance (e.g., 3D spatial resolution, noise, and contrast) - taking two specific examples in IG brachytherapy and IG vertebroplasty. For IG brachytherapy, a procedure-specific task is constructed which tests the performance of flat-panel cone-beam CT in measuring the volumetric distribution of Pd-103 permanent implant seeds in relation to neighboring bone and soft-tissue structures in a pelvis phantom. For IG interventional procedures, a procedure-specific task is constructed in the context of vertebroplasty performed on a cadaverized ovine spine, demonstrating the volumetric image quality in pre-, intra-, and post-therapeutic images of the region of interest and testing the performance of the system in measuring the volumetric distribution of bone cement (PMMA) relative to surrounding spinal anatomy. Each of these tasks highlights numerous promising and challenging aspects of flat-panel cone-beam CT applied to IG procedures.
Foremost among the promising imaging performance characteristics of cone-beam CT using flat-panel imagers is the ability to form volumetric images with soft-tissue contrast visibility in combination with sub-millimeter 3-D spatial resolution. Each of these two essential characteristics is intimately related to the spatial-frequency-dependent signal and noise transfer characteristics of the imaging system. Therefore a thorough, quantitative analysis of the 3-D noise-equivalent quanta (NEQ) and detective quantum efficiency (DQE) is essential to understanding the volumetric imaging performance of such systems, identifying the factors that limit performance, and revealing their full potential. This paper presents investigation of the 3-D NEQ and DQE for volume CT systems based on direct and indirect-detection flat-panel imagers (FPIs). Classical descriptions of image noise in transaxial CT are extended to the case of non-ideal 2-D detectors and 3-D image reconstruction. Definitions of NEQ and DQE are extended to provide figures of merit for 3-D imaging performance. A complex interplay between the system transfer functions, 3-D noise aliasing, and the 3-D DQE is uncovered, revealing several important phenomena: (1) 3-D NPS aliasing is a significant factor in the reconstruction process affecting DQE; (2) the degree of 3-D NPS aliasing is different for direct and indirect-detection FPIs and is related in non-trivially to the detector MTF and reconstruction filter; (3) the 3-D NEQ depends significantly on the choice of reconstruction filter - in contrast to the classical notion that NEQ is independent of such - and the effect is wholly attributable to 3-D NPS aliasing; and (4) the 3-D DQE for volume reconstructions is asymmetric between transverse and sagittal/coronal planes. Results for 3-D NEQ and DQE are integrated with 3-D spatial-frequency-dependent descriptions of imaging task (e.g., ideal observer detection and/or discrimination tasks) to yield the 3-D detectability index, helping to bridge the gap between NEQ and the performance of model observers.
The author describes a two-stage technique for 3-D camera calibration using off-the-shelf TV cameras and lenses. The technique is aimed at efficient computation of the external position and orientation of the camera relative to the object reference coordinate system as well as its effective focal length, radial lens distortion and image scanning parameters. A critical review of the state of the art is given and it is shown that the two-stage technique has advantages in terms of accuracy, speed and versatility. A theoretical framework is established and supported by comprehensive proof Test results using real data are described. Both accuracy and speed are reported. A 388 multiplied by 480 CCD camera calibrated by this technique performed several 3-D measurement with an average accuracy of 1/4000 over the field of view, or 1/8000 over the depth. The experimental results are analyzed and compared with theoretical prediction.
Flat-panel imager (FPI) based cone-beam computed tomography (CBCT) is a strong candidate technology for intraoperative imaging in image-guided procedures such as brachytherapy. The soft-tissue imaging performance and potential navigational utility have been investigated using a computer-controlled benchtop system. These early results have driven the development of an isocentric C-arm for intraoperative FPI-CBCT, capable of collecting 94 projections over 180 degrees in 110 seconds. The C-arm system employs a large-area FPI (41x41 cm 2) with 400 micron pixel pitch and Gd 2 O 2 S:Tb scintillator. Image acquisition, processing and reconstruction are orchestrated under a single Windows-based application. Reconstruction is performed by a modified Feldkamp algorithm implemented on a high-speed reconstruction engine (CBR-1500-2, Terarecon, Inc. San Mateo, CA). Non-idealities in the source and detector trajectories during orbital motion has been quantified and tested for stability. Cone-beam CT imaging performance was tested through both quantitative and qualitative methods. The system MTF was measured using a wire phantom and demonstrated frequency pass out to 0.6 mm -1 . Voxel noise was measured at 2.7% in a uniform 12 cm diameter water bath. Anatomical phantoms were employed for qualitative evaluation of the imaging performance. Images of an anesthesized rabbit demonstrated the capacity of the system to discern soft-tissue structures within a living subject while offering sub-millimeter spatial resolution. The dose delivered in each of the imaging procedures was estimated from in-air exposure measurements to be ~ 0.1 cGy (center of 12 cm water cylinder). Imaging studies of an anthropomorphic prostate phantom were performed with and without radioactive seeds (~80 Pd-103 sources). Soft-tissue imaging performance and seed detection appear to satisfy the imaging and navigation requirements for image-guided brachytherapy. These investigations advance the development and evaluation of such technology for image-guided surgical procedures, including brachytherapy, vertebroplasty and neurosurgery. The demonstrated soft-tissue visibility, excellent spatial resolution, low imaging dose, and convenient form factor make C-arm based cone-beam CT a powerful new technology for image-guidance applications.
BACKGROUND
Stereotactic radiation therapy is highly effective in the treatment of small brain metastases, regardless of the histology. This suggests that small extracranial malignancies may be curable with similar radiation therapy. The authors developed a novel treatment unit for administering such therapy.METHODS
The unit consisted of a linear accelerator (linac), an X-ray simulator (X-S), computed tomography (CT), and a table. The gantry axes of the three machines were coaxial and could be matched by rotating the table. Patients were instructed to perform shallow respiration with oxygen. The motion of the tumor was monitored with the X-S. When the motion was slight enough, the table was rotated to the CT. To include all geometric movement on the CT images, each scan was made while the patient was performing shallow respiration. After the CT positioning, the table was rotated to the linac, and non-coplanar treatment was given. Beginning in October 1994, 45 patients with 23 primary or 43 metastatic lung carcinomas were treated. Radiation doses at the 80% isodose line were 30-75 gray in 5-15 fractions over 1-3 weeks with or without conventional radiation therapy.RESULTSThe treatment was performed with no or minimal adverse acute symptoms. The daily treatment time was short. During a median follow-up of 11 months, local progression occurred in 2 of 66 lesions. Interstitial changes in the lung were limited.CONCLUSIONS
With this unit and procedure, focal radiation therapy similar to stereotactic radiation therapy is possible for extracranial sites. The preliminary experience appeared safe and promising, and further exploration of this approach is warranted. Cancer 1998;82:1062-70. © 1998 American Cancer Society.
Stereotactic radiation therapy is highly effective in the treatment of small brain metastases, regardless of the histology. This suggests that small extracranial malignancies may be curable with similar radiation therapy. The authors developed a novel treatment unit for administering such therapy.
The unit consisted of a linear accelerator (linac), an X-ray simulator (X-S), computed tomography (CT), and a table. The gantry axes of the three machines were coaxial and could be matched by rotating the table. Patients were instructed to perform shallow respiration with oxygen. The motion of the tumor was monitored with the X-S. When the motion was slight enough, the table was rotated to the CT. To include all geometric movement on the CT images, each scan was made while the patient was performing shallow respiration. After the CT positioning, the table was rotated to the linac, and non-coplanar treatment was given. Beginning in October 1994, 45 patients with 23 primary or 43 metastatic lung carcinomas were treated. Radiation doses at the 80% isodose line were 30-75 gray in 5-15 fractions over 1-3 weeks with or without conventional radiation therapy.
The treatment was performed with no or minimal adverse acute symptoms. The daily treatment time was short. During a median follow-up of 11 months, local progression occurred in 2 of 66 lesions. Interstitial changes in the lung were limited.
With this unit and procedure, focal radiation therapy similar to stereotactic radiation therapy is possible for extracranial sites. The preliminary experience appeared safe and promising, and further exploration of this approach is warranted.
An earlier paper [Simpson et al., Med. Phys. 9, 574 (1982)] described a computed tomography (CT) scanner that was constructed by adding a detector array to a 4-MV isocentric linear accelerator. Since the previous article, the detector array has been improved and we now demonstrate better than 3-mm spatial resolution and better than 1% relative electron density discrimination. A series of pictures from volunteer patients is included. Normal anatomy is visualized with bone, muscle, fat, and air being clearly delineated.
In this paper the importance of correcting a small centre-of-rotation displacement (approximately 1 mm) in single-photon-emission computed tomography (SPECT) using high-resolution pinhole collimation is demonstrated. A filtered backprojection (FBP) algorithm is derived for a pinhole geometry that has a displaced centre-of-rotation. The centre-of-rotation displacement, or mechanical shift (MS), is the displacement of the midplane of the pinhole collimator from the rotation centre. It is characterized by two orthogonal components: the shift eta of the midplane of the pinhole collimator along the direction of the axis of rotation, and the distance tau between the midline of the pinhole collimator and the axis of rotation. This algorithm is fast and corrects the centre-of-rotation displacement directly by incorporating this displacement into the algorithm. This new algorithm is evaluated using both a three-line source and a micro-SPECT cold rod phantom. The results demonstrate that the pinhole FBP with mechanical shift correction is able to correct the 'doughnut'-type artifacts caused by the mechanical shift and restore the expected system resolution.
A filtered backprojection (FBP) algorithm is derived based on Feldkamp's FBP algorithm for a cone beam geometry that has a displaced center of rotation. In cone beam single photon emission computed tomography (CB-SPECT) the center of rotation displacement can degrade the reconstructed images. The center of rotation displacement of interest is mechanical shift, which is the displacement of the midplane of the cone beam collimator off the rotation center. Mechanical shift is characterized by two orthogonal components: the shift of the midplane of the cone beam collimator along the direction of the axis of rotation, and the distance between the midline of the cone beam collimator and the axis of rotation. This new algorithm corrects mechanical shift directly by incorporating mechanical shift into the algorithm. This new algorithm is evaluated using both Monte Carlo simulated data and experimentally acquired data. The results demonstrate that this algorithm is able to correct for blurring and the "doughnut" type artifacts caused by system mechanical shift and improve the image resolution.
Reconstructing a three-dimensional (3D) object from a set of its two-dimensional (2D) X-ray projections requires that the source position and image plane orientation in 3D space be obtained with high accuracy. We present a method for estimating the geometrical parameters of an X-ray imaging chain, based on the minimization of the reprojection mean quadratic error measured on reference points of a calibration phantom. This error is explicitly calculated with respect to the geometrical parameters of the conic projection, and a conjugate gradient technique is used for its minimization. By comparison to the classical unconstrained method, better results were obtained in simulation with our method, specially when only a few reference points are available. This method may be adapted to different X-ray systems and may also be extended to the estimation of the geometrical parameters of the imaging chain trajectory in the case of dynamic acquisitions.
This study used a standard commercial electronic portal imaging device (EPID) area detector attached to an isocentric linear accelerator and the Feldkamp algorithm to produce cone beam tomographic reconstructions. The EPID has a active area of 32.5 x 32.5 cm2, and can record 12-bit images using two monitor units (MU), with a resolution of 2.1 x 2.0 mm2 FWHM. Since the EPID was not large enough to record the full patient projection at about 1.5 geometric magnification, it was necessary to offset the detector to collect half-cone projections. Corrections are required to convert pixel values into units of exit dose and to realign the projections to overcome the +/- 4 mm support arm sag. With a geometric magnification of 1.5 the sensitive volume is a cylinder of radius 21 cm and length 17 cm. Unfortunately, the patient couch contains metal bed support rails that lie just outside this cylinder, and produce streak artefacts in the reconstruction. Using 90 views the system delivers a central dose of 90 cGy, and has a density resolution of 4%.
A filtered backprojection algorithm is developed for single photon emission computed tomography (SPECT) imaging with an astigmatic collimator having a displaced center of rotation. The astigmatic collimator has two perpendicular focal lines, one that is parallel to the axis of rotation of the gamma camera and one that is perpendicular to this axis. Using SPECT simulations of projection data from a hot rod phantom and point source arrays, it is found that a lack of incorporation of the mechanical shift in the reconstruction algorithm causes errors and artifacts in reconstructed SPECT images. The collimator and acquisition parameters in the astigmatic reconstruction formula, which include focal lengths, radius of rotation, and mechanical shifts, are often partly unknown and can be determined using the projections of a point source at various projection angles. The accurate determination of these parameters by a least squares fitting technique using projection data from numerically simulated SPECT acquisitions is studied. These studies show that the accuracy of parameter determination is improved as the distance between the point source and the axis of rotation of the gamma camera is increased. The focal length of the focal line perpendicular to the axis of rotation is determined more accurately than the focal length to the focal line parallel to this axis.
Although electronic portal imaging devices (EPIDs) are efficient tools for radiation therapy verification, they only provide images of overlapped anatomic structures. We investigated using a fluorescent screen/CCD-based EPID, coupled with a novel multi-level scheme algebraic reconstruction technique (MLS-ART), for a feasibility study of portal computed tomography (CT) reconstructions. The CT images might be useful for radiation treatment planning and verification. We used an EPID, set it to work at the linear dynamic range and collimated 6 MV photons from a linear accelerator to a slit beam of 1 cm wide and 25 cm long. We performed scans under a total of approximately 200 monitor units (MUs) for several phantoms in which we varied the number of projections and MUs per projection. The reconstructed images demonstrated that using the new MLS-ART technique megavoltage portal CT with a total of 200 MUs can achieve a contrast detectibility of approximately 2.5% (object size 5 mm x 5 mm) and a spatial resolution of 2.5 mm.
In their tomotherapy concept Mackie and co-workers proposed not only a new technique for IMRT but also an appropriate and satisfactory method of treatment verification. This method allows both monitoring of the portal dose distribution and imaging of the patient anatomy during treatment by means of online CT. This would enable the detection of inaccuracies in dose delivery and patient set-up errors. In this paper results are presented showing that a single electronic portal imaging device (EPID) could deliver all data necessary to establish such a complete verification system for tomotherapy and even other IMRT techniques. Consequently it has to be shown that it is able to record both the low-intensity photon fluences encountered in tomographic imaging and the intense photon transmission of each treatment field.
The detector under investigation is a video-based EPID, the BIS 710 (manufactured by Wellh?fer Dosimetrie, Schwarzenbruck, Germany). To examine the suitability of the BIS for CT at 6 MV beam quality, different phantoms were scanned and reconstructed.
The agreement between a diamond detector and BIS responses is quantitative. Tomographic reconstruction of a complete set of these transmission profiles resulted in images which resolve 3 cm large objects having a (theoretical) contrast to water of less than 9%. Three millimetre objects with a 100% contrast are clearly visible. The BIS signal was shown to measure photon fluence distributions. The reconstructed images possess a spatial and contrast resolution sufficient for accurate imaging of the patient anatomy, needed for treatment verification in many clinical cases.
Purpose:
Dose escalation in conformal radiation therapy requires accurate field placement. Electronic portal imaging devices are used to verify field placement but are limited by the low subject contrast of bony anatomy at megavoltage (MV) energies, the large imaging dose, and the small size of the radiation fields. In this article, we describe the in-house modification of a medical linear accelerator to provide radiographic and tomographic localization of bone and soft-tissue targets in the reference frame of the accelerator. This system separates the verification of beam delivery (machine settings, field shaping) from patient and target localization.
Materials and methods:
A kilovoltage (kV) x-ray source is mounted on the drum assembly of an Elekta SL-20 medical linear accelerator, maintaining the same isocenter as the treatment beam with the central axis at 90 degrees to the treatment beam axis. The x-ray tube is powered by a high-frequency generator and can be retracted to the drum-face. Two CCD-based fluoroscopic imaging systems are mounted on the accelerator to collect MV and kV radiographic images. The system is also capable of cone-beam tomographic imaging at both MV and kV energies. The gain stages of the two imaging systems have been modeled to assess imaging performance. The contrast-resolution of the kV and MV systems was measured using a contrast-detail (C-D) phantom. The dosimetric advantage of using the kV imaging system over the MV system for the detection of bone-like objects is quantified for a specific imaging geometry using a C-D phantom. Accurate guidance of the treatment beam requires registration of the imaging and treatment coordinate systems. The mechanical characteristics of the treatment and imaging gantries are examined to determine a localizing precision assuming an unambiguous object. MV and kV radiographs of patients receiving radiation therapy are acquired to demonstrate the radiographic performance of the system. The tomographic performance is demonstrated on phantoms using both the MV and the kV imaging system, and the visibility of soft-tissue targets is assessed.
Results and discussion:
Characterization of the gains in the two systems demonstrates that the MV system is x-ray quantum noise-limited at very low spatial frequencies; this is not the case for the kV system. The estimates of gain used in the model are validated by measurements of the total gain in each system. Contrast-detail measurements demonstrate that the MV system is capable of detecting subject contrasts of less than 0.1% (at 6 and 18 MV). A comparison of the kV and MV contrast-detail performance indicates that equivalent bony object detection can be achieved with the kV system at significantly lower doses (factors of 40 and 90 lower than for 6 and 18 MV, respectively). The tomographic performance of the system is promising; soft-tissue visibility is demonstrated at relatively low imaging doses (3 cGy) using four laboratory rats.
Conclusions:
We have integrated a kV radiographic and tomographic imaging system with a medical linear accelerator to allow localization of bone and soft-tissue structures in the reference frame of the accelerator. Modeling and experiments have demonstrated the feasibility of acquiring high-quality radiographic and tomographic images at acceptable imaging doses. Full integration of the kV and MV imaging systems with the treatment machine will allow on-line radiographic and tomographic guidance of field placement.
The image quality of 3D reconstructions produced using a C-arm mounted XRII depends on precise determination of the geometric parameters that describe the detector system in the laboratory frame of reference. We have designed a simplified calibration system that depends on images of a metal sphere, acquired during rotation of the gantry through 200 degrees. Angle-dependent shift corrections are obtained, accounting for nonideal motion in two directions: perpendicular to the axis of rotation and tangential to the circular trajectory (tau), and parallel to the axis of rotation (xi). Projection images are corrected prior to reconstruction using a simple shift-interpolation algorithm. We show that the motion of the gantry is highly reproducible during acquisitions within one day (mean standard deviation in tau and xi is 0.11 mm and 0.08 mm, respectively), and over 21 months (mean standard deviation in tau and xi is 0.10 mm and 0.06 mm, respectively). Reconstruction of a small-bead phantom demonstrates uniformity of the correction algorithm over the full volume of the reconstruction [standard deviation of full-width-half-maximum of the beads is approximately 0.25 pixels (0.13 mm) over the volume of reconstruction]. Our approach provides a simple correction technique that can be applied when trajectory deviations are significant relative to the pixel size of the detector but small relative to the detector field of view, and when the fan angle of the acquisition geometry is small (<20 degrees). A comparison with other calibration techniques in the literature is provided.
This paper is about calibration of cone-beam (CB) scanners for both x-ray computed tomography and single-photon emission computed tomography. Scanner calibration refers here to the estimation of a set of parameters which fully describe the geometry of data acquisition. Such parameters are needed for the tomographic reconstruction step. The discussion is limited to the usual case where the cone vertex and planar detector move along a circular path relative to the object. It is also assumed that the detector does not have spatial distortions. We propose a new method which requires a small set of measurements of a simple calibration object consisting of two spherical objects, that can be considered as 'point' objects. This object traces two ellipses on the detector and from the parametric description of these ellipses, the calibration geometry can be determined analytically using explicit formulae. The method is robust and easy to implement. However, it is not fully general as it is assumed that the detector is parallel to the rotation axis of the scanner. Implementation details are given for an experimental x-ray CB scanner.
The thermal and thermo-mechanical (fatigue) properties of a stationary-anode kilovoltage x-ray source that can be integrated into the head of a medical linear accelerator have been modeled. A finite element program has been used to model two new target designs. The first design makes minor modifications to the existing target assembly of a Varian medical linear accelerator, while the second design adds an additional cooling tube, changes the target angle, and uses a tungsten-rhenium alloy rather than tungsten as the kilovoltage target material. The thermal calculations have been used to generate cyclic stress/strain values from which estimates of fatigue in the target designs have been made. Both kilovoltage and megavoltage operation have been studied. Analysis of the megavoltage operation shows that there are only small differences in the thermal and fatigue characteristics after the target assembly is modified to include a kilovoltage target. Thus, megavoltage operation should not be compromised. The first kilovoltage target design can handle a 900 W heat load (e.g., 120 kVp, 7.5 mA, 2 x 2 mm2 source size); the heat load being limited by the temperature at the surface of the cooling tubes and mechanical fatigue at the surface of the target. The second design can handle a 1250 W heat load (e.g., 120 kVp, approximately 10.4 mA, 2 x 2 mm2 source size). Our calculations show that installation of a kilovoltage x-ray target is practical from thermal and thermo-mechanical perspectives.
The use of cone-beam computed tomography (CBCT) has been proposed for guiding the delivery of radiation therapy, and investigators have examined the use of both kilovoltage (kV) and megavoltage (MV) x-ray beams in the development of such CBCT systems. In this paper, the inherent contrast and signal-to-noise ratio (SNR) performance for a variety of existing and hypothetical detectors for CBCT are investigated analytically as a function of imaging dose and object size. Theoretical predictions are compared to the results of experimental investigations employing largearea flat-panel imagers (FPIs) at kV and MV energies. Measurements were performed on two different FPI-based CBCT systems: a bench-top prototype incorporating an FPI and kV x-ray source (100 kVp x rays), and a system incorporating an FPI mounted on the gantry of a medical linear accelerator (6 MV x rays). The SNR in volume reconstructions was measured as a function of dose and found to agree reasonably with theoretical predictions. These results confirm the theoretically predicted advantages of employing kV energy x rays in imaging soft-tissue structures found in the human body. While MV CBCT may provide a valuable means of correcting 3D setup errors and may offer an advantage in terms of simplicity of mechanical integration with a linear accelerator (e.g., implementation in place of a portal imager), kV CBCT offers significant performance advantages in terms of image contrast and SNR per unit dose for visualization of soft-tissue structures. The relatively poor SNR performance at MV energies is primarily a result of the low x-ray quantum efficiencies (approximately a few percent or less) that are currently achieved with FPIs at high energies. Furthermore, kV CBCT with an FPI offers the potential of combined volumetric and radiographic/fluoroscopic imaging using the same device.
Geometric uncertainties in the process of radiation planning and delivery constrain dose escalation and induce normal tissue complications. An imaging system has been developed to generate high-resolution, soft-tissue images of the patient at the time of treatment for the purpose of guiding therapy and reducing such uncertainties. The performance of the imaging system is evaluated and the application to image-guided radiation therapy is discussed.
A kilovoltage imaging system capable of radiography, fluoroscopy, and cone-beam computed tomography (CT) has been integrated with a medical linear accelerator. Kilovoltage X-rays are generated by a conventional X-ray tube mounted on a retractable arm at 90 degrees to the treatment source. A 41 x 41 cm(2) flat-panel X-ray detector is mounted opposite the kV tube. The entire imaging system operates under computer control, with a single application providing calibration, image acquisition, processing, and cone-beam CT reconstruction. Cone-beam CT imaging involves acquiring multiple kV radiographs as the gantry rotates through 360 degrees of rotation. A filtered back-projection algorithm is employed to reconstruct the volumetric images. Geometric nonidealities in the rotation of the gantry system are measured and corrected during reconstruction. Qualitative evaluation of imaging performance is performed using an anthropomorphic head phantom and a coronal contrast phantom. The influence of geometric nonidealities is examined.
Images of the head phantom were acquired and illustrate the submillimeter spatial resolution that is achieved with the cone-beam approach. High-resolution sagittal and coronal views demonstrate nearly isotropic spatial resolution. Flex corrections on the order of 0.2 cm were required to compensate gravity-induced flex in the support arms of the source and detector, as well as slight axial movements of the entire gantry structure. Images reconstructed without flex correction suffered from loss of detail, misregistration, and streak artifacts. Reconstructions of the contrast phantom demonstrate the soft-tissue imaging capability of the system. A contrast of 47 Hounsfield units was easily detected in a 0.1-cm-thick reconstruction for an imaging exposure of 1.2 R (in-air, in absence of phantom). The comparison with a conventional CT scan of the phantom further demonstrates the spatial resolution advantages of the cone-beam CT approach.
A kV cone-beam CT imaging system based on a large-area, flat-panel detector has been successfully adapted to a medical linear accelerator. The system is capable of producing images of soft tissue with excellent spatial resolution at acceptable imaging doses. Integration of this technology with the medical accelerator will result in an ideal platform for high-precision, image-guided radiation therapy.
The development and performance of a system for x-ray cone-beam computed tomography (CBCT) using an indirect-detection flat-panel imager (FPI) is presented. Developed as a bench-top prototype for initial investigation of FPI-based CBCT for bone and soft-tissue localization in radiotherapy, the system provides fully three-dimensional volumetric image data from projections acquired during a single rotation. The system employs a 512 x 512 active matrix of a-Si:H thin-film transistors and photodiodes in combination with a luminescent phosphor. Tomographic imaging performance is quantified in terms of response uniformity, response linearity, voxel noise, noise-power spectrum (NPS), and modulation transfer function (MTF), each in comparison to the performance measured on a conventional CT scanner. For the geometry employed and the objects considered, response is uniform to within 2% and linear within 1%. Voxel noise, at a level of approximately 20 HU, is comparable to the conventional CT scanner. NPS and MTF results highlight the frequency-dependent transfer characteristics, confirming that the CBCT system can provide high spatial resolution and does not suffer greatly from additive noise levels. For larger objects and/or low exposures, additive noise levels must be reduced to maintain high performance. Imaging studies of a low-contrast phantom and a small animal (a euthanized rat) qualitatively demonstrate excellent soft-tissue visibility and high spatial resolution. Image quality appears comparable or superior to that of the conventional scanner. These quantitative and qualitative results clearly demonstrate the potential of CBCT systems based upon flat-panel imagers. Advances in FPI technology (e.g., improved x-ray converters and enhanced electronics) are anticipated to allow high-performance FPI-based CBCT for medical imaging. General and specific requirements of kilovoltage CBCT systems are discussed, and the applicability of FPI-based CBCT systems to tomographic localization and image-guidance for radiotherapy is considered.
Techniques are described for calibrating certain intrinsic camera parameters for machine vision. The parameters to be calibrated are the horizontal scale factor, and the image center. The scale factor calibration uses a one-dimensional fast Fourier transform and is accurate and efficient. It also permits the use of only one coplanar set of calibration points for general camera calibration. Three groups of techniques for center calibration are presented: Group I requires using a laser and a four-degree-of-freedom adjustment of its orientation, but is simplest in concept and is accurate and reproducible; Group II is simple to perform, but is less accurate than the other two; and the most general, Group II, is accurate and efficient, but requires a good calibration plate and accurate image feature extraction of calibration points. Group II is recommended most highly for machine vision applications. Results of experiments are presented and compared with theoretical predictions. Accuracy and reproducibility of the calibrated parameters are reported, as well as the improvement in actual 3-D measurement due to center calibration
A method is presented for estimating the geometrical parameters of cone beam systems with multiple heads, each head having its own orientation. In tomography, for each head, the relative position of the rotation axis and of the collimator do not change during the data acquisition. One thus can separate the parameters into intrinsic parameters and extrinsic parameters. The intrinsic parameters describe the detection system geometry and the extrinsic parameters the position of the detection system with respect to the rotation axis. Intrinsic parameters are measured directly, once for each collimator. Extrinsic parameters must be estimated each time the acquisition geometry is modified. Extrinsic parameters are estimated by minimizing the distances between the measured position of a point source projection and the computed position obtained using the estimated extrinsic parameters. The main advantage of this method is that the extrinsic parameters are only weakly correlated when the intrinsic parameters are known. Thus one can use any simple least square error minimization method to perform the estimation of the extrinsic parameters. Giving a fixed value to the distance between the point source and the rotation axis in the estimation process, ensures the coherence of the extrinsic parameters between each head. The authors show that, with this calibration method, the full width at half maximum measured with point sources is very close to the theoretical one, and remains almost unchanged when more than one head is used. Simulation results and reconstructions on a Jaszczak phantom are presented that show the capabilities of this method.< >
Astigmatic single photon emission computed tomography imaging with a displaced center of rota-tion Flat-panel cone-beam CT: A novel imaging technology for image guided procedures Flat-panel cone-beam CT on a mobile isocentric C-arm for image guided brachytherapy
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Flat-panel cone-beam CT on a mobile isocentric C-arm for image guided brachytherapy Three-dimensional computed tomographic reconstruction using a C-arm mounted XRII: Image-based correction of gantry motion nonidealities
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A novel technique to characterize the complete motion of a linear accelerator
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Geometric calibration of cone‐beam computerized tomography system and medical linear accelerator
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A novel technique to characterize the complete motion of a linear accelerator
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