基于压缩感知理论的医学图像重构算法研究现状  

Research of the Medical Image Reconstruction Algorithm Based on Compressed Sensing

作　　者：李修寒 朱松盛[1] 

机构地区：[1]南京医科大学基础医学院生物医学工程系,南京210029

出　　处：《生物医学工程学进展》2014年第4期216-218,242,共4页Progress in Biomedical Engineering

基　　金：江苏省高校自然科学研究基金资助项目(10KJD310001);大学生创新创业训练计划项目(201410312062X)

摘　　要：压缩感知理论的提出促进了医学成像技术的发展。压缩感知是通过直接采集压缩后的数据,利用重构算法高精度恢复原信号,避免了传统的先采样再压缩造成的资源浪费。基于压缩感知的CT、MRI、US成像的重构算法对其应用于医学成像起着至关重要的作用。因此,对重构算法进行了着重介绍,并进行比较分析。The compressed sensing theory has promoted the development of medical imaging technology. Compressed sensing theory is to restore the original signal with high accuracy using reconstruction algorithm after di- rectly acquiring the compressed data, which avoids the waste of resources caused by traditional theory. Image re- construction algorithm of CT, MRI, US based on compressed sensing plays important roles in medical imaging. Therefore, this paper introduces and comparatively analyzes reconstruction algorithms.

关 键 词：压缩感知 医学成像 重构算法 高精度 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]