Stopping Rules for Algebraic Iterative Reconstruction Methods in Computed Tomography

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Abstract

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.
Original languageEnglish
Title of host publicationProceedings of 21st International Conference on Computational Science and Its Applications (ICCSA)
PublisherIEEE
Publication date2022
Pages60-70
Article number9732394
ISBN (Print)978-1-6654-5844-3
DOIs
Publication statusPublished - 2022
Event21st International Conference on Computational Science and Its Applications - University of Cagliari, Cagliari, Italy
Duration: 13 Sep 202116 Sep 2021
Conference number: 21
https://2021.iccsa.org/

Conference

Conference21st International Conference on Computational Science and Its Applications
Number21
LocationUniversity of Cagliari
Country/TerritoryItaly
CityCagliari
Period13/09/202116/09/2021
Internet address

Keywords

  • Tomographic reconstruction
  • Iterative methods
  • Stopping rules
  • Semi-convergence

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