Stopping Rules for Algebraic Iterative Reconstruction Methods in Computed Tomography
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 ha...
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creator | Hansen, Per Christian Jørgensen, Jakob Sauer Rasmussen, Peter Winkel |
description | 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. |
doi_str_mv | 10.48550/arxiv.2106.10053 |
format | Article |
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(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.</description><identifier>DOI: 10.48550/arxiv.2106.10053</identifier><language>eng</language><subject>Computer Science - Numerical Analysis ; Mathematics - Numerical Analysis ; Mathematics - Optimization and Control</subject><creationdate>2021-06</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2106.10053$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2106.10053$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Hansen, Per Christian</creatorcontrib><creatorcontrib>Jørgensen, Jakob Sauer</creatorcontrib><creatorcontrib>Rasmussen, Peter Winkel</creatorcontrib><title>Stopping Rules for Algebraic Iterative Reconstruction Methods in Computed Tomography</title><description>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.</description><subject>Computer Science - Numerical Analysis</subject><subject>Mathematics - Numerical Analysis</subject><subject>Mathematics - Optimization and Control</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz71qwzAUQGEtGUrSB-hUvYBdW7IsdQymP4GUQurdXElXjsC2jCyH5u1L005nO_AR8lAWeaWEKJ4gfvtLzsqizsuiEPyOtF8pzLOfenpaB1yoC5Huhx51BG_oIWGE5C9IT2jCtKS4muTDRD8wnYNdqJ9oE8Z5TWhpG8bQR5jP1x3ZOBgWvP_vlrSvL23znh0_3w7N_phBLXkmnagUWiUYQqWFkQoRWf3MBHcGNCgLqA13wjEr68qV0jKnmXKyglqg5lvy-Le9sbo5-hHitfvldTce_wFrT00N</recordid><startdate>20210618</startdate><enddate>20210618</enddate><creator>Hansen, Per Christian</creator><creator>Jørgensen, Jakob Sauer</creator><creator>Rasmussen, Peter Winkel</creator><scope>AKY</scope><scope>AKZ</scope><scope>GOX</scope></search><sort><creationdate>20210618</creationdate><title>Stopping Rules for Algebraic Iterative Reconstruction Methods in Computed Tomography</title><author>Hansen, Per Christian ; Jørgensen, Jakob Sauer ; Rasmussen, Peter Winkel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a673-7f548ed852ea4b5c78eee269253fcaba8daebc3f5f2d764f17d2fb28f74a65eb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Computer Science - Numerical Analysis</topic><topic>Mathematics - Numerical Analysis</topic><topic>Mathematics - Optimization and Control</topic><toplevel>online_resources</toplevel><creatorcontrib>Hansen, Per Christian</creatorcontrib><creatorcontrib>Jørgensen, Jakob Sauer</creatorcontrib><creatorcontrib>Rasmussen, Peter Winkel</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv Mathematics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hansen, Per Christian</au><au>Jørgensen, Jakob Sauer</au><au>Rasmussen, Peter Winkel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Stopping Rules for Algebraic Iterative Reconstruction Methods in Computed Tomography</atitle><date>2021-06-18</date><risdate>2021</risdate><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.</abstract><doi>10.48550/arxiv.2106.10053</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Numerical Analysis Mathematics - Numerical Analysis Mathematics - Optimization and Control |
title | Stopping Rules for Algebraic Iterative Reconstruction Methods in Computed Tomography |
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