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

Publication: Research - peer-review › Journal article – Annual report year: 2012

### Standard

**Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm.** / Sidky, Emil Y.; Jørgensen, Jakob Heide; Pan, Xiaochuan.

Publication: Research - peer-review › Journal article – Annual report year: 2012

### Harvard

*Physics in Medicine and Biology*, vol 57, pp. 3065–3091. DOI: 10.1088/0031-9155/57/10/3065

### APA

*Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm*.

*Physics in Medicine and Biology*,

*57*, 3065–3091. DOI: 10.1088/0031-9155/57/10/3065

### CBE

### MLA

*Physics in Medicine and Biology*. 2012, 57. 3065–3091. Available: 10.1088/0031-9155/57/10/3065

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### Author

### Bibtex

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### RIS

TY - JOUR

T1 - Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm

AU - Sidky,Emil Y.

AU - Jørgensen,Jakob Heide

AU - Pan,Xiaochuan

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

U2 - 10.1088/0031-9155/57/10/3065

DO - 10.1088/0031-9155/57/10/3065

M3 - Journal article

VL - 57

SP - 3065

EP - 3091

JO - Physics in Medicine and Biology

T2 - Physics in Medicine and Biology

JF - Physics in Medicine and Biology

SN - 0031-9155

ER -