稀疏信号恢复理论在CT图像重建中的应用

基金项目:

国家自然科学基金(60672104)

973课题(2006CB705705)

北京市共建项目

详细信息

The Application of Sparse Signal Recovery Theory in CT Image Reconstruction

1. Department of Information Research, Institute of Information Engineering, Information Engineering University, Zhengzhou 450002, China;
2. Department of Electronic Science and Technology, Institute of Information Engineering, Information Engineering University, Zhengzhou 450002, China;
3. The Beijing City Key Lab of Medical Physics&Engineering, Peking University, Beijing 100871, China

摘要: 新的图像重建算法一直是CT成像前沿研究中的热点问题之一,而实际中常常遇到的有限角度重建问题则是其中的难点。Terence Tao和他的同事提出了一种稀疏信号恢复理论,为解决这个问题提出了可能的应用策略。我们在本文中介绍了这个理论并给出了在锥束CT重建中应用的初步结果。这种理论和策略的实现对很多应用情况都有重要的意义,为该领域的发展开辟了新的方向,也必将对该领域的发展产生重大影响。
- CT /
- 图像重建算法 /
- 稀疏信号恢复 /
- 有限角度重建
Abstract: The new image reconstruction algorithm remains one of the hot problems in the current research of computed tomography(CT),among which the reconstruction algorithm with limited views is a difficult problem in practice.Recently,a sparse signal recovery theory was proposed by Terence Tao and his colleagues,which may give a strategy for solving this problem.We introduced this theory and presented some primary simulated results in this paper.The realization of the strategy is significant in some special applications for cone beam CT imaging,which will be a new direction in this field and will greatly influence on this field.
- CT /
- image reconstruction algorithm /
- sparse signal reconstruction /
- limited-views reconstruction