HPC for iterative image reconstruction in CT
Proceedings of the 2008 C3S2E conference
Limited view CT reconstruction and segmentation via constrained metric labeling
Computer Vision and Image Understanding
Line-source based X-ray tomography
Journal of Biomedical Imaging
A novel weighted least squares PET image reconstruction method using adaptive variable index sets
Digital Signal Processing
Mapping iterative medical imaging algorithm on cell accelerator
Journal of Biomedical Imaging - Special issue on Parallel Computation in Medical Imaging Applications
AIR Tools - A MATLAB package of algebraic iterative reconstruction methods
Journal of Computational and Applied Mathematics
Journal of Biomedical Imaging
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Computed tomography (CT) has been extensively studied for years and widely used in the modern society. Although the filtered back-projection algorithm is the method of choice by manufacturers, efforts are being made to revisit iterative methods due to their unique advantages, such as superior performance with incomplete noisy data. In 1984, the simultaneous algebraic reconstruction technique (SART) was developed as a major refinement of the algebraic reconstruction technique (ART). However, the convergence of the SART has never been established since then. In this paper, the convergence is proved under the condition that coefficients of the linear imaging system are nonnegative. It is shown that from any initial guess the sequence generated by the SART converges to a weighted least square solution.