南方医科大学学报2018，Vol.38Issue(1)：48-54,7.
基于噪声相关性的惩罚加权最小二乘算法在低剂量数字乳腺层析成像中的应用
Low-dose digital breast tomosynthsis imaging via noise correlation based penalized weighted least-squares algorithm
摘要
Abstract
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. Conclusion The proposed method can significantly reduce noise and improve the quality of DBT images.关键词
数字乳腺层析成像/低剂量/噪声相关性/加权最小二乘Key words
digital breast tomosynthesis/low-dose/noise correlation/weighted least squares algorithm引用本文复制引用
陈美玲,陶熙,李华勇,陈武凡,张华..基于噪声相关性的惩罚加权最小二乘算法在低剂量数字乳腺层析成像中的应用[J].南方医科大学学报,2018,38(1):48-54,7.基金项目
国家自然科学基金(81501466) （81501466）
广东省自然科学基金(2015A030310018) （2015A030310018）
广州市科技计划项目(201710010099) Supported by National Natural Science Foundation of China (81501466). （201710010099）
