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Compared methods. Similarity measure acronyms: CC = neighborhood cross-correlation, Mean Squares = mean squared difference, MI = mutual information.
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Cancer is a highly lethal disease that is mainly treated by image-guided radiotherapy. Because the low dose of cone beam CT is less harmful to patients, cone beam CT images are often used for target delineation in image-guided radiotherapy of various cancers, especially in breast and lung cancer. However, breathing and heartbeat can cause position...
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... is the most used medical image registration toolkit with very good performance. An overview of the compared methods and similarity terms is given in Table 1. Among them, Affine denotes the affine transformation-based method, Electronics 2022Electronics , 11, 1862 Rigid denotes the rigid transformation-based method, Similarity denotes the rotation and uniform scaling transformation-based method, and SyN denotes the symmetric diffeomorphic transformation-based method. ...Citations
... When IGRT-based treatment is implemented, some image technologies need to be used to supervise and guide the whole treatment process. Due to this process often requiring multiple acquisitions and analyses of images, CBCT, with its lower imaging dose, is usually used as the guidance image to reduce the harm to the patient [9,10]. In IGRT, the most important step is to analyze the position information between the CBCT image and the delineated CT images; that is, the radiologist needs to register and align the CBCT and the CT images. ...
... 2(10) More details about Equation (10) can be found in our previous work[17]. ...
Unlike the high imaging radiation dose of computed tomography (CT), cone-beam CT (CBCT) has smaller radiation dose and presents less harm to patients. Therefore, CBCT is often used for target delineation, dose planning, and postoperative evaluation in the image-guided radiotherapy (IGRT) of various cancers. In the process of IGRT, CBCT images usually need to be collected multiple times in a radiotherapy stage for postoperative evaluation. The effectiveness of radiotherapy is measured by comparing and analyzing the registered CBCT and the source CT image obtained before radiotherapy. Hence, the registration of CBCT and CT is the most important step in IGRT. CBCT images usually have poor visual effects due to the small imaging dose used, which adversely affects the registration performance. In this paper, we propose a novel adaptive visual saliency feature enhancement method for CBCT in IGRT. Firstly, we denoised CBCT images using a structural similarity based low-rank approximation model (SSLRA) and then enhanced the denoised results with a visual saliency feature enhancement (VSFE)-based method. Experimental results show that the enhancement performance of the proposed method is superior to the comparison enhancement algorithms in visual objective comparison. In addition, the extended experiments prove that the proposed enhancement method can improve the registration accuracy of CBCT and CT images, demonstrating their application prospects in IGRT-based cancer treatment.
... The self-calibration method based on reconstructed image features uses the feature information of the reconstructed image as the criterion to iteratively solve the geometric parameters through constant updates and realize geometric artifact calibration [10,11]. In 2013, Jun et al. [12] proposed a geometric artifact self-calibration method using highfrequency energy. ...
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.
