摘要
电阻抗图象重建是一个严重病态的反问题，特别是当重建模型的有限单元数增大时，重建图象会变差，甚至发散。提出一种全新的基于空间滤波理论的正则化方法，它不依赖于阻抗分布的先验估计，因此它比最大后验（ＭＡＰ）正则化方法易于实现；而且计算机模拟实验结果表明，利用这种新的正则化方法重建的动态阻抗图象质量好于ｉｋｈｏｎｏｖ正则化方法。
Image reconstruction in electrical impedance tomography (EIT) is a highly ill-posed inverse problem. Especially, the reconstructed images will become bad, even divergent, as the finite elements in the reconstructed model increase. We developed a new regularization method based on the spatial filtering theory, which is independent on the estimation of impedance distribution. So it can be implemented easier than the maximum a posteriori(MAP) method, and the computer simulation results demonstrate that the quality of the reconstructed dynamic impedance images with the new regularization method is better than with Tikhonov method.
出处
《计算机工程》
CAS
CSCD
北大核心
2001年第9期14-16,共3页
Computer Engineering
基金
国家自然科学基金
上海市高校科技发展基金资助项目
关键词
正则化方法
电阻抗成象
图象重建
反问题
CT
医学
Regularization method
Electrical impedance tomography
Image reconstruction
Inverse problem
Ill-posed
