Technical Note: Proximal Ordered Subsets Algorithms for TV Constrained Optimization in CT Image Reconstruction

TL;DR

This paper provides detailed implementation guidance and parameter selection suggestions for proximal ordered subsets algorithms used in TV-constrained CT image reconstruction, supplementing prior work on noise properties.

Contribution

It introduces detailed pseudo-code and practical recommendations for implementing ordered subsets algorithms in TV-constrained CT reconstruction.

Findings

Enhanced understanding of algorithm implementation

Practical parameter selection guidelines

Improved reproducibility of CT reconstruction methods

Abstract

This article is intended to supplement our 2015 paper in Medical Physics titled "Noise properties of CT images reconstructed by use of constrained total-variation, data-discrepancy minimization", in which ordered subsets methods were employed to perform total-variation constrained data-discrepancy minimization for image reconstruction in X-ray computed tomography. Here we provide details regarding implementation of the ordered subsets algorithms and suggestions for selection of algorithm parameters. Detailed pseudo-code is included for every algorithm implemented in the original manuscript.