Efficient primal-dual algorithm for imaging applications with matrix stacking, applied to DBT image reconstruction

Fuente: arXiv
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Main Authors: Sidky, Emil Y., Phillips, John Paul, Zhang, Zheng, Xia, Dan, Reiser, Ingrid S., Pan, Xiaochuan
Format: Preprint
Published: 2026
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author Sidky, Emil Y.
Phillips, John Paul
Zhang, Zheng
Xia, Dan
Reiser, Ingrid S.
Pan, Xiaochuan
author_facet Sidky, Emil Y.
Phillips, John Paul
Zhang, Zheng
Xia, Dan
Reiser, Ingrid S.
Pan, Xiaochuan
contents The primal-dual hybrid gradient (PDHG) algorithm for solving convex optimization problems that arise in tomographic imaging is revisited. In particular, simplification of the selection of step-size parameters is developed for optimization problems with multiple terms, each containing a linear transform subject to splitting. This simplification maintains algorithm efficiency while avoiding massive grid searches for the optimal parameter settings. The PDHG framework is demonstrated on an image reconstruction problem for wide-angle digital breast tomosythesis (DBT); use of the proposed optimization problem is enabled by the framework and it is demonstrated to have some advantage in quantitative accuracy of the reconstructed volume and in improving DBT depth resolution.
format Preprint
id arxiv_https___arxiv_org_abs_2604_23063
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Efficient primal-dual algorithm for imaging applications with matrix stacking, applied to DBT image reconstruction
Sidky, Emil Y.
Phillips, John Paul
Zhang, Zheng
Xia, Dan
Reiser, Ingrid S.
Pan, Xiaochuan
Optimization and Control
Medical Physics
The primal-dual hybrid gradient (PDHG) algorithm for solving convex optimization problems that arise in tomographic imaging is revisited. In particular, simplification of the selection of step-size parameters is developed for optimization problems with multiple terms, each containing a linear transform subject to splitting. This simplification maintains algorithm efficiency while avoiding massive grid searches for the optimal parameter settings. The PDHG framework is demonstrated on an image reconstruction problem for wide-angle digital breast tomosythesis (DBT); use of the proposed optimization problem is enabled by the framework and it is demonstrated to have some advantage in quantitative accuracy of the reconstructed volume and in improving DBT depth resolution.
title Efficient primal-dual algorithm for imaging applications with matrix stacking, applied to DBT image reconstruction
topic Optimization and Control
Medical Physics
url https://arxiv.org/abs/2604.23063