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arXiv · 2605.29133

Improving depth-resolution, in-plane contrast, and reducing non-uniformity artifacts for wide-angle DBT

Emil Y. Sidky·Adrian A. Sanchez·John Paul Phillips·Zheng Zhang·Dan Xia·Ingrid S. Reiser·Xiaochuan Pan
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Abstract

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.

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Emil Y. Sidky, Adrian A. Sanchez, John Paul Phillips, Zheng Zhang, Dan Xia, Ingrid S. Reiser, Xiaochuan Pan. 2026-05-27. Improving depth-resolution, in-plane contrast, and reducing non-uniformity artifacts for wide-angle DBT. https://arxiv.org/abs/2605.29133

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