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Conference Paper: Low-dose X-ray computed tomography image reconstruction using edge sparsity regularization

TitleLow-dose X-ray computed tomography image reconstruction using edge sparsity regularization
Authors
Luo, ShoushengKang, KekeWang, YangTai, Xue Cheng
KeywordsADMM
Edge sparsity regularization
Low dose
XCT image reconstruction
Issue Date2019
Citation
ACM International Conference Proceeding Series, 2019, p. 303-307 How to Cite?
DOI: http://dx.doi.org/10.1145/3364836.3364898
AbstractTotal variation (TV) regularization is one of popular techniques for low dose x-ray computed tomography image reconstruction. However, the reconstruction image by TV method often suffers staircase effect. In this paper, we propose an edge sparsity model, which penalizes the difference between L1 norm and L2 norm of gradient, for low dose x-ray computed tomography image reconstruction. Alternating direction method of multipliers (ADMM) is adopted to solve the proposed model. Experiment results on simulation data and real data are presented to verify the effectiveness of the proposed method.
Persistent Identifierhttp://hdl.handle.net/10722/363345

 

DC FieldValueLanguage
dc.contributor.authorLuo, Shousheng-
dc.contributor.authorKang, Keke-
dc.contributor.authorWang, Yang-
dc.contributor.authorTai, Xue Cheng-
dc.date.accessioned2025-10-10T07:46:10Z-
dc.date.available2025-10-10T07:46:10Z-
dc.date.issued2019-
dc.identifier.citationACM International Conference Proceeding Series, 2019, p. 303-307-
dc.identifier.urihttp://hdl.handle.net/10722/363345-
dc.description.abstractTotal variation (TV) regularization is one of popular techniques for low dose x-ray computed tomography image reconstruction. However, the reconstruction image by TV method often suffers staircase effect. In this paper, we propose an edge sparsity model, which penalizes the difference between L<sup>1</sup> norm and L<sup>2</sup> norm of gradient, for low dose x-ray computed tomography image reconstruction. Alternating direction method of multipliers (ADMM) is adopted to solve the proposed model. Experiment results on simulation data and real data are presented to verify the effectiveness of the proposed method.-
dc.languageeng-
dc.relation.ispartofACM International Conference Proceeding Series-
dc.subjectADMM-
dc.subjectEdge sparsity regularization-
dc.subjectLow dose-
dc.subjectXCT image reconstruction-
dc.titleLow-dose X-ray computed tomography image reconstruction using edge sparsity regularization-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1145/3364836.3364898-
dc.identifier.scopuseid_2-s2.0-85077542711-
dc.identifier.spage303-
dc.identifier.epage307-

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