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Combined visualization of a brain tumor, the white matter tractography and the functional areas associated with motor tasks. The tumor is surrounded by a safety area, which is used to filter and color the fibers in the tractography. Both the tumor and the activation areas directly influence the color of the fibers.
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The surgical removal of brain tumors can lead to functional impairment. Therefore it is crucial to minimize the damage to important functional areas during surgery. These areas can be mapped before surgery by using functional MRI. However, functional impairment is not only caused by damage to these areas themselves. It is also caused by damage to t...
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Context 1
... that are more brightly colored pass closer to the tumor. Figure 10 shows two more examples for comparison: on the left color across the fiber reflects the distance of that point from the tumor and on the right each fiber is colored according to its shortest distance. ...
Context 2
... mode shows the the explicit relationship between fiber bundles and fMRI activation areas. As shown in Figure 11, each fMRI activation area is automatically colored with a distinct color and can be rendered using several different rendering methods as explained in Section 4.3. Fibers that intersect with an activation area are assigned the same color as that activation area. ...
Context 3
... of the three visualization modes described above can be used during exploration of fused MRI, fMRI and DTI datasets. For example, in Figure 12 the tumor and its safety zone are shown along with a number of fMRI activa- tion areas. Fibers that pass through the tumor safety zone have been colored turquoise, whereas tumors passing through activation areas but not through in the vicinity of the tumor have been colored the same as the activation areas. ...
Similar publications
Purpose:
Diffusion Tensor Imaging (DTI) is a powerful imaging technique that has led to improvements in the diagnosis and prognosis of cerebral lesions and neurosurgical guidance for tumor resection. Traditional tensor modeling, however, has difficulties in differentiating tumor-infiltrated regions and peritumoral edema. Here, we describe the supe...
Citations
... Using DT images jointly with fMRI and regular MR scans could further improve the quality of surgical planning as fiber tracts and functional regions of the brain around the tumor could be analyzed. DTI, fMRI, and regular MRIs are combined and visualized with volume rendering and tubebased rendering for brain tumor resection planning [115]. Fiber bundles can be interactively selected so that those around the tumor could be avoided in the planning. ...
Importance . Medical images are essential for modern medicine and an important research subject in visualization. However, medical experts are often not aware of the many advanced three-dimensional (3D) medical image visualization techniques that could increase their capabilities in data analysis and assist the decision-making process for specific medical problems. Our paper provides a review of 3D visualization techniques for medical images, intending to bridge the gap between medical experts and visualization researchers. Highlights . Fundamental visualization techniques are revisited for various medical imaging modalities, from computational tomography to diffusion tensor imaging, featuring techniques that enhance spatial perception, which is critical for medical practices. The state-of-the-art of medical visualization is reviewed based on a procedure-oriented classification of medical problems for studies of individuals and populations. This paper summarizes free software tools for different modalities of medical images designed for various purposes, including visualization, analysis, and segmentation, and it provides respective Internet links. Conclusions . Visualization techniques are a useful tool for medical experts to tackle specific medical problems in their daily work. Our review provides a quick reference to such techniques given the medical problem and modalities of associated medical images. We summarize fundamental techniques and readily available visualization tools to help medical experts to better understand and utilize medical imaging data. This paper could contribute to the joint effort of the medical and visualization communities to advance precision medicine.
... and their technique was specifically focused on functional brain images [RTFE+06]. Their tool was aimed at supporting cognitive neuroscientists in experimen- Figure 22: Fiber bundle filtering using multiple boxes that can be combined to select bundles using arbitrary logic combinations for selection of fibers to be shown in multimodal visualization [BBMN+07]. ...
... tal studies and to communicate results to non-experts and employs a template brain with patient-specific fMRI data (see Figure 21). Blaas et al. proposed an approach that fuses fMRI and DTI data for planning brain tumor resections [BBMN+07]. In this fused volume, users can extract fiber bundles that pass through a region around the tumor. ...
This thesis presents selected applications with the aim of visually enhancing
focus structures. It covers four different applications with a
clear problem statement. The solution is anything but simple. Thus, four applications will be presented and analyzed, complemented by their respective solutions. Novel visualization techniques to enhance focus structures will be presented. Furthermore, two overviews of the current state of the art are described, which cover the fields of illustrative
visualization techniques and multimodal data visualization.
... They superimposed functional correlatives and DTI measures on a 2D slice with the purpose of comparing spatial distribution of mutual peaks. Later, Blass et al. visualized and explored 3D functional areas and fiber tracts in the vicinity of a tumor to preserve adjacent eloquent areas 35 in a surgical case [11]. Similarly, Greicius et al. and van den Heuvel et al. employed deterministic fiber tractography to investigate the existence of con- nective pathways among distant regions of the Default Mode Network (DMN) [12] [13]. ...
Background:
Construction of brain functional and structural networks by neuroimaging methods facilitates inter-modal studies. These type of studies often demand exploration tools to carry out functional-structural discoveries and answer questions regarding the anatomical basis of brain networks.
New method:
This paper describes the design and development of a software module for interactive visualization and exploration of dual-modal brain networks. Our objective was to equip the user with a research tool to investigate brain connectivity matrices while visualizing relevant anatomical landmarks within a 3D volumetric view. In order to create this view, MultiXplore was designed to load data from both structural and diffusion MRI and connectivity matrices.
Results:
Once user starts to select desired cells through an interactive matrix unit, associated axonal fiber pathways and grey matter regions are generated and displayed. Integration and visualization of functional and structural networks in this 3D interactive framework was successfully implemented and tested.
Comparison with existing method(s):
MultiXplore contributes to the transition of connectivity visualization techniques from node-link format to an anatomically more realistic graphical form and assists scientists in relating connectivity matrices to their anatomical correlates. This module also benefits from additional novel functionalities to annotate and differentiate fibers in a large bundle. Unlike traditional graph displays, interactive functionality helps in the inspection and visualization of relevant structures without cluttering the scene with excessive items.
Conclusion:
This module was designed and developed as a plugin to 3D Slicer imaging platform and is accessible for neuroimaging researchers through NITRC (http://www.nitrc.org/projects/multixplore/).
... Their tool was aimed at supporting cognitive neuroscientists in experimental studies and to communicate results to non-experts and employs a template brain with patient-specific fMRI data. Blaas et al. proposed an approach that fuses fMRI and DTI data for planning brain tumor resections [131]. In this fused volume, users can extract fiber bundles that pass through a region around the tumor. ...
This thesis deals with visualizing anatomical data for medical education and surgical planning purposes. To this end, we have developed a detailed virtual atlas, the Virtual Surgical Pelvis (VSP), which unifies surgically relevant knowledge on pelvic anatomy. We provide methods to share the knowledge contained in the VSP for educational purposes, and to visualize the VSP in the context of individual patients for pre-operative planning purposes.
... Preoperative planning in neurosurgery is an active field of research [12,91,107,108]. In multimodal visualizations, one powerful way to highlight inner structures are cutting techniques. ...
... Several approaches for a combined visualization exist [41,53]. Fiber selection methods [11,12,61] result in a fiber subset that cross a specific region. The winning entry of the visualization contest [24] introduced a surgery planning tool including an exploration and an in-detail inspection step similar to the steps presented in this work. ...
... 12: Different samplings of the q-space: Green points indicate image sequences defined by a specific q-vector. Sampling the whole sphere requires qvectors with varying b-values (3.12a), whereas shell-sampling uses a constant b-value (3.12b). ...
... Joshi et al. [2008] enhances the techniques described by Rieder et al. [2008] by presenting different shapes of access paths (spherical, cubical, and ellipsoidal) and visualizing SPECT activation regions and the position of electrodes. Another considerable work in the field of interactive risk exploration that is focused on the analysis of fiber tracks (DTI) and functional areas around a tumor is described in Blaas et al. [2007]. Fiber bundles that pass through a region around a tumor are detected and can be filtered and color-enhanced depending on the tumor distance or the distance to a functional area. ...
... Image registration [2,3,4,5] plays an essential role in various medical imaging applications, such as fusion of images from different modalities [6,7], super-resolution in positron emission tomography (PET) imaging [8], visualizing diffusion tensor MR images (DTI) [9,10], atlas based segmentation [11,12], geometric correction of functional magnetic resonance imaging (fMRI) [13], pattern recognition [14], etc. The purpose of image registration in these applications is to establish the correspondence among the pixels/voxels of image pairs. 1 Many existing nonrigid image registration methods are based on physical models such as elastic model proposed by Briot [15], diffusion image registration [16], viscous fluid model proposed by Christensen [17], and curverture based image registration [18]. ...
... Other possible applications are fusion of images from different modalities [6,7], super-resolution in positron emission tomography (PET) imaging [8], visualizing diffusion tensor MR images (DTI) [9,10], atlas based segmentation [11,12], geometric correction of functional magnetic resonance imaging (fMRI) [13], pattern recognition [14], etc. The purposed image registration in these applications is to establish the correspondence among the pixels/voxels of image pairs. ...
Multi-modal data of the complex human anatomy contain a wealth of information. To visualize and explore such data, techniques for emphasizing important structures and controlling visibility are essential. Such fused overview visualizations guide physicians to suspicious regions to be analysed in detail, e.g. with slice-based viewing. We give an overview of state of the art in multi-modal medical data visualization techniques. Multi-modal medical data consist of multiple scans of the same subject using various acquisition methods, often combining multiple complimentary types of information. Three-dimensional visualization techniques for multi-modal medical data can be used in diagnosis, treatment planning, doctor–patient communication as well as interdisciplinary communication. Over the years, multiple techniques have been developed in order to cope with the various associated challenges and present the relevant information from multiple sources in an insightful way. We present an overview of these techniques and analyse the specific challenges that arise in multi-modal data visualization and how recent works aimed to solve these, often using smart visibility techniques. We provide a taxonomy of these multi-modal visualization applications based on the modalities used and the visualization techniques employed. Additionally, we identify unsolved problems as potential future research directions.
The term e-Science describes computational and data-intensive science. It has become a complementary experiment paradigm alongside the traditional in vivo and in vitro experiment paradigms. e-Science opens new doors for scientists and with it, it exposes a number of challenges such as how to organize huge datasets and coordinate distributed execution. For these challenges, a plethora of technologies and innovations have come together to enable e-Science (Foster and Kesselman 2006). Nowadays, complex scientific experiments designed following the e-Science paradigm are preformed using geographically distributed instruments, data and computing resources. The newly designed scientific experiments are costly, time-consuming, and multidisciplinary. Complex scientific experiments not only require access to geographically distributed hardware and software resources, but also extensive support to foster best practices, dissemination, and re-use.
