Purpose: This work aims to develop an image reconstruction algorithm for wide-angle digital breast tomosynthesis (DBT) that has improved depth resolution and in-plane contrast while reducing non-uniformity artifacts. Approach: The image reconstruction algorithm is an extension of our prior work on sparsity-regularized iterative image reconstruction. The algorithm is performed in two stages as explained in a prior work. The first stage consists of a low-resolution reconstruction that exploits sparsity for quantitative accuracy. In this work, this first stage is augmented with a formulation that includes the estimation of a "background" image, which absorbs low-frequency artifacts that cause image non-uniformity. Results: The new algorithm is demonstrated on a patient case for which the data are acquired on a wide-angle DBT system. Conclusion: The results on the shown case indicate that the algorithm design goals have been met, but additional empirical results and task-based assessment are needed to strengthen this conclusion.
@article{arxiv.2605.29133,
title = {Improving depth-resolution, in-plane contrast, and reducing non-uniformity artifacts for wide-angle DBT},
author = {Emil Y. Sidky and Adrian A. Sanchez and John Paul Phillips and Zheng Zhang and Dan Xia and Ingrid S. Reiser and Xiaochuan Pan},
journal= {arXiv preprint arXiv:2605.29133},
year = {2026}
}
Comments
Submitted to the Journal of Medical Imaging special issue: Pioneers in Medical Imaging: Honoring the Memory of Harrison H. Barrett, PhD