Journal of X-Ray Science and Technology - Volume 27, issue 2
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Impact Factor 2019: 1.662
Journal of X-Ray Science and Technology is an international journal designed for the diverse community (biomedical, industrial and academic) of users and developers of novel x-ray imaging techniques. The purpose of the journal is to provide clear and full coverage of new developments and applications in the field.
Areas such as x-ray microlithography, x-ray astronomy and medical x-ray imaging as well as new technologies arising from fields traditionally considered unrelated to x rays (semiconductor processing, accelerator technology, ionizing and non-ionizing medical diagnostic and therapeutic modalities, etc.) present opportunities for research that can meet new challenges as they arise.
Abstract: BACKGROUND: Automatic segmentation of pulmonary vascular tree in the thoracic computed tomography (CT) image is a promising but challenging task with great clinical potential values. It is difficult to segment the whole vascular tree in reasonable time and acceptable accuracy. OBJECTIVE: To develop a novel pulmonary vessel segmentation approach by incorporating vessel enhancement filters and the anisotropic diffusion filter with the variational region growing. METHODS: First, the airway wall from the lung lobes is eliminated from CT images by using multi-scale morphological operations. Second, a Hessian-based multi-scale vesselness filter and medialness filter are applied to detect…and enhance the potential vessel. Third, an anisotropic diffusion filter is used to remove noise and enhance the tube-like structures in CT images. Last, the vascular tree is segmented by applying variational region growing algorithm. RESULTS: Applying to the CT images collected from the entire dataset of VESSEL12 challenge, we achieved an average sensitivity of 92.9%, specificity of 91.6% and the area under the ROC curve of AUC = 0.972. CONCLUSIONS: This study demonstrated feasibility of segmenting the pulmonary vessel effectively by incorporating vessel enhancement filters and the anisotropic diffusion filter with the variational region growing algorithm. Our method cannot only segment both large and peripheral vessels, but also distinguish the vessels from the adjacent tissues, especially the airway walls.
Abstract: In radiotherapy, dose distributions are obtained by using dose calculation algorithms that are implanted in treatment planning systems (TPS). This study aims to compare the surface doses of separate field sizes calculated by different version of The Analytical Anisotropic Algorithm (AAA) and measured by the parallel-plate ion chamber that is admitted as the most reliable dosimetry system for the surface region dose measurements. In order to measure the near surface dose, water equivalent solid phantom was used and measurements were made for 6MV photon beam at 100 cm source-detector distance for 5×5, 10×10, and 20×20 cm2 field sizes. AAA 8.9 and…AAA 15.1 versions of the Varian Eclipse TPS were used for surface dose calculations by generating beams with separate field sizes. The doses were read by considering the effective buildup thickness of Markus parallel-plate ion chamber. The surface doses using 6 MV photon beams for 10×10 cm2 field size at 0.07 mm were found to be 11.04%, 26.25%, and 19.69% for AAA v8.9, AAA v15.1 and Markus chamber, respectively. It was seen that for both of the AAA versions and Markus parallel-plate ion chamber, increasing field sizes also increase surface dose. For all field sizes, surface dose was lowest by using AAA v8.9 at 0.07 mm. The different versions of the same TPS algorithms may calculate the surface doses distinctively. After upgrading of TPS algorithms, surface doses should be calculated and compared by measurements with different dosimetry systems to better understand their calculation behaviors in the near surface region.
Keywords: AAA dose algorithm, surface dose, buildup region, Markus parallel plate ion chamber
Abstract: Total variation (TV) regularization-based iterative reconstruction algorithms have an impressive potential to solve limited-angle computed tomography with insufficient sampling projections. The analysis of exact reconstruction sampling conditions for a TV-minimization reconstruction model can determine the minimum number of scanning angle and minimize the scanning range. However, the large-scale matrix operations caused by increased testing phantom size are the computation bottleneck in determining the exact reconstruction sampling conditions in practice. When the size of the testing phantom increases to a certain scale, it is very difficult to analyze quantitatively the exact reconstruction sampling condition using existing methods. In this paper, we…propose a fast and efficient algorithm to determine the exact reconstruction sampling condition for large phantoms. Specifically, the sampling condition of a TV minimization model is modeled as a convex optimization problem, which is derived from the sufficient and necessary condition of solution uniqueness for the L1 minimization model. An effective alternating direction minimization algorithm is developed to optimize the objective function by alternatively solving two sub-problems split from the convex problem. The Cholesky decomposition method is used in solving the first sub-problem to reduce computational complexity. Experimental results show that the proposed method can efficiently solve the verification problem of the accurate reconstruction sampling condition. Furthermore, we obtain the lower bounds of scanning angle range for the exact reconstruction of a specific phantom with the larger size.
Keywords: Sampling condition, limited-angle accurate reconstruction, alternating direction minimization algorithm, Cholesky decomposition method
Abstract: Contrast-enhanced multi-slice computed tomography (MSCT) is commonly used in the diagnosis of complex malignant tumours. This technology provides comprehensive and accurate information about tumour size and shape in relation to solid tumours and the affected adjacent organs and tissues. This case report demonstrates the benefit of using MSCT 3D imaging for preoperative planning in a patient with late-stage (T4) sarcomatoid renal cell carcinoma, a rare renal malignant tumour. The surgical margin on the liver was negative, and no metastases to veins, lungs or other organs were detected by abdominal and chest contrast-enhanced CT. Although sarcomatoid histology is considered to be…a poor prognostic factor, the patient is alive and well 17 months after surgery. The MSCT imaging modality enables 3D rendering of an area of interest, which assists surgical decision-making in cases of advanced renal tumours. In this case, as a result of MSCT 3D reconstruction, the patient received justified surgical treatment without compromising oncological principles.