Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm

The primal-dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1-26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems for the...

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Published inPhysics in medicine & biology Vol. 57; no. 10; pp. 3065 - 3091
Main Authors Sidky, Emil Y, Jørgensen, Jakob H, Pan, Xiaochuan
Format Journal Article
LanguageEnglish
Published England IOP Publishing 21.05.2012
Subjects
Algorithms
convex optimization
CT image reconstruction
Image Processing, Computer-Assisted - methods
Mammography
Phantoms, Imaging
Poisson Distribution
primal-dual methods
Tomography, X-Ray Computed - methods
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Summary:The primal-dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1-26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems for the purpose of designing iterative image reconstruction algorithms for CT. The primal-dual algorithm is briefly summarized in this paper, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application modeling breast CT with low-intensity x-ray illumination is presented.
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ISSN:0031-9155
1361-6560
DOI:10.1088/0031-9155/57/10/3065