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Updated: Oct 2, 2026
Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research
Published on: January 12, 2013
Improving depth-resolution, in-plane contrast, and reducing non-uniformity artifacts for wide-angle DBT
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 three patient cases for which the data are acquired on a wide-angle DBT system.
Conclusion:
The results on the shown cases indicate that the algorithm design goals have been met, but additional empirical results and task-based assessment are needed to strengthen this conclusion.
