Conference paper
Stopping Rules for Algebraic Iterative Reconstruction Methods in Computed Tomography
Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark1
Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark3
Algebraic models for the reconstruction problem in X-ray computed tomography (CT) provide a flexible framework that applies to many measurement geometries. For large-scale problems we need to use iterative solvers, and we need stopping rules for these methods that terminate the iterations when we have computed a satisfactory reconstruction that balances the reconstruction error and the influence of noise from the measurements.
Many such stopping rules are developed in the inverse problems communities, but they have not attained much attention in the CT world. The goal of this paper is to describe and illustrate four stopping rules that are relevant for CT reconstructions.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2022 |
| Pages: | 60-70 |
| Proceedings: | 21<sup>st</sup> International Conference on Computational Science and Its Applications |
| ISBN: | 1665458437 , 9781665458436 , 1665458445 and 9781665458443 |
| Types: | Conference paper |
| DOI: | 10.1109/ICCSA54496.2021.00019 |
| ORCIDs: | Hansen, Per Christian , Jørgensen, Jakob Sauer and Rasmussen, Peter Winkel |
CT reconstructions Computed tomography Measurement uncertainty Noise measurement Reconstruction algorithms Scientific computing Software X-ray computed tomography algebra algebraic iterative reconstruction methods computerised tomography image reconstruction inverse problems inverse problems communities iterative methods large-scale problems measurement geometries medical image processing reconstruction error semi-convergence stopping rules tomographic reconstruction
