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[Low-dose digital breast tomosynthsis imaging via noise correlation based penalized weighted least-squares algorithm]
Meiling Chen1,2, Xi Tao1,2, Huayong Li1,2
1Department of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China.
Objective:
To achieve low-dose digital breast tomosynthsis (DBT) projection recovery using penalized weighted least square algorithm incorporating accurate modeling of the variance of the projection data and noise correlation in the flat panel detector.
Methods:
Models were established for the quantal noise and electronic noise in the DBT system to construct the penalized weighted least squares algorithm based on noise correlation for projection data restoration. The filter back projection algorithm was then used for DBT image reconstruction.
Results:
The reconstruction results of the ACR phantom data at different dose levels showed a good performance of the proposed method in noise suppression and detail preservation. CNRs and LSNRs of the reconstructed images from the restored projections were increased by about 3.6 times compared to those of reconstructed images from the original projections.
Conclusions:
The proposed method can significantly reduce noise and improve the quality of DBT images.
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