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17 October 2022 Iterative image reconstruction for CT with unmatched projection matrices using the generalized minimal residual algorithm
Emil Y. Sidky, Per Christian Hansen, Jakob S. Jørgensen, Xiaochuan Pan
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Proceedings Volume 12304, 7th International Conference on Image Formation in X-Ray Computed Tomography; 1230406 (2022) https://doi.org/10.1117/12.2646511
Event: Seventh International Conference on Image Formation in X-Ray Computed Tomography (ICIFXCT 2022), 2022, Baltimore, United States
Abstract
The generalized minimal residual (GMRES) algorithm is applied to image reconstruction using linear computed tomography (CT) models. The GMRES algorithm iteratively solves square, non-symmetric linear systems and it has practical application to CT when using unmatched back-projector/projector pairs and when applying preconditioning. The GMRES algorithm is demonstrated on a 3D CT image reconstruction problem where it is seen that use of unmatched projection matrices does not prevent convergence, while using an unmatched pair in the related conjugate gradients for least-squares (CGLS) algorithm leads to divergent iteration. Implementation of preconditioning using GMRES is also demonstrated.
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Emil Y. Sidky, Per Christian Hansen, Jakob S. Jørgensen, and Xiaochuan Pan "Iterative image reconstruction for CT with unmatched projection matrices using the generalized minimal residual algorithm", Proc. SPIE 12304, 7th International Conference on Image Formation in X-Ray Computed Tomography, 1230406 (17 October 2022); https://doi.org/10.1117/12.2646511
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KEYWORDS
Computed tomography
Reconstruction algorithms
Image restoration
Matrices
Image quality
CT reconstruction
Image processing
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