收稿日期: 2004-06-08
修回日期: 2004-09-15
网络出版日期: 2005-07-15
PET Image Analysis Based on Wavelet Transform
Received date: 2004-06-08
Revised date: 2004-09-15
Online published: 2005-07-15
Supported by
supported by the Major State Basic Research Development Program of China (G1999054000),the Knowledge Innovation Project of Chinese Academy of Sciences (U5163)
提出一种把小波变换和统计检验结合起来检测PET图像激活区的方法.首先,采用模拟的PET图像来评价算法的可靠性,结果显示,在小波域上进行统计检验比传统的直接在空间域上进行统计检验具有更高的灵敏度,更强的抗噪声干扰性能,更快的计算速度.最后,用该方法处理真实的PET图像,也得到了满意的结果.该方法为PET医学图像处理和脑功能研究提供了一种新的多尺度、高性能的分析手段,对于脑功能研究的功能区定位、临床诊断、药物疗效评估等有着重要意义
关键词： 小波变换; t-检验; 正电子发射计算机断层成像; 激活区
闫镔 , 王鹏 , 李可 , 郝晶 , 吴义根 , 谢千河 , 支联合 , 王崴 , 鲁娜 , 袁秀丽 , 单保慈 . 基于小波变换的PET图像分析(英文)[J]. 中国科学院大学学报, 2005 , 22(4) : 499 -505 . DOI: 10.7523/j.issn.2095-6134.2005.4.016
In this paper wavelet transform and test of hypothesis are combined to detect activated areas in PET images.The algorithm is validated by using the simulation images under different conditions. Compared with the spatial domain algorithm, the wavelet domain algorithm can get more precise results, better SNR trait and more rapid computing speed.The probability of type Ⅱ error in wavelet domain is less than that in the spatial domain, so the wavelet domain algorithm is a kind of sensitive algorithm. Finally, we used this algorithm to process the real PET images and achieved good result.This algorithm may result in important significance to the detection of functional areas, the clinic diagnosis and the evaluation of curative effect.
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