Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm
Abstract
The primal-dual optimization algorithm developed in Chambolle and Pock (CP), 2011 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 the article, 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.
Cite
@article{arxiv.1111.5632,
title = {Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm},
author = {Emil Y. Sidky and Jakob H. Jørgensen and Xiaochuan Pan},
journal= {arXiv preprint arXiv:1111.5632},
year = {2015}
}
Comments
Resubmitted to Physics in Medicine and Biology. Text has been modified according to referee comments, and typos in the equations have been corrected