Iterative image reconstruction for CT with unmatched projection matrices using the generalized minimal residual algorithm
Medical Physics
2022-05-04 v2
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.
Cite
@article{arxiv.2201.07408,
title = {Iterative image reconstruction for CT with unmatched projection matrices using the generalized minimal residual algorithm},
author = {Emil Y. Sidky and Per Christian Hansen and Jakob S. Jørgensen and Xiaochuan Pan},
journal= {arXiv preprint arXiv:2201.07408},
year = {2022}
}
Comments
Accepted to the 2022 CT Meeting