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脑功能区自动提取法对99mTc-ECD脑显像63个脑区的灰度分析
引用本文:郭万华,张剑戈,江旭峰,申景涛,贾支俊,许守林,王成. 脑功能区自动提取法对99mTc-ECD脑显像63个脑区的灰度分析[J]. 中国临床医学影像杂志, 2006, 17(11): 601-603
作者姓名:郭万华  张剑戈  江旭峰  申景涛  贾支俊  许守林  王成
作者单位:1. 南京大学医学院附属南京鼓楼医院核医学科,江苏,南京,210008
2. 上海交通大学基础医学部生物医学工程教研室,上海,200025
3. 上海交通大学附属瑞金医院核医学科,上海,200025
摘    要:目的:验证脑解剖功能区的自动提取法在99mTc-ECD脑显像中提取位置准确性,并初步探讨63个功能区药物相对摄取分布。方法:采用图像配准和图像形变方法,将99mTc-ECD脑SPECT图像标化到标准的Talairach坐标空间,按各脑部功能区对全脑中坐标点分类,计算每个脑区摄取信息即平均灰度,并计算其与全脑平均灰度比值,比较左右半球及不同脑区间摄取比值差异。结果:该方法成功地将目标图像与标准坐标空间配准,提取的脑功能区通过不同透视显示与实际目测的功能区吻合,通过对63个脑解剖区分析,人的大脑左右对99mTc-ECD摄取是不对称的,各个脑区间的分布悬殊也很大,枕叶楔前叶、舌回以及顶下小叶等在脑内99mTc-ECD摄取最高,而眶回、胼胝体以及尾状核尾部摄取最低。结论:脑功能区自动提取法对99mTc-ECD脑显像对特定脑区分析显示快速,准确,重现性好的特点,不但适合多样本统计分析,也适宜于单个样本的处理,为研究特定脑感兴趣区提供了一个客观、细致的分析方法。

关 键 词:脑;体层摄影术  发射型计算机  单光子
文章编号:1008-1062(2006)11-0601-03
收稿时间:2006-03-13
修稿时间:2006-03-13

Brain functional area automatic extraction method for 99mTc-ECD SPECT imaging
GUO Wan-hua,ZHANG Jian-ge,JIANG Xu-feng,SHEN Jing-tao,JIA Zhi-jun,XU Shou-lin,WANG Cheng. Brain functional area automatic extraction method for 99mTc-ECD SPECT imaging[J]. Journal of China Clinic Medical Imaging, 2006, 17(11): 601-603
Authors:GUO Wan-hua  ZHANG Jian-ge  JIANG Xu-feng  SHEN Jing-tao  JIA Zhi-jun  XU Shou-lin  WANG Cheng
Abstract:Objective: To verify the accuracy of brain anatomic and functional area extraction method for 99mTc-ECD SPECT imaging, and preliminary assess the 99mTc-ECD distribution among the 63 functional areas in the brain. Methods: By image registration and deformation, the 99mTc-ECD SPECT images are mapped into Talairach space, and the individual brain functional area's coordinates are classified, so that each area average gray scale can be calculated, also the gray scale difference between half brain of left and right is compared. Results: The 99mTc-ECD brain images are successfully registered into the standard Talairach coordinates space, the anatomic and functional areas are extracted, which can be rendered perspectively in the SPECT image template, and the position relation is close to the area drawn by the eye. The uptake of the 99mTc-ECD is asymmetric between the left and the right for most of brain area, and even in the same part of brain, the uptake for this trace is quite different among the fields of brain. The precuneus, lingual gyrus and inferior parietal lobule are ranked the top three according to the 99mTc-ECD distribution, meanwhile the orbital gyrus, corpus callosum and the caudate tail are the least three area for the trace uptake. Conclusion: The brain automatically extract can analyze the brain different area quickly, correctly and repetitively. This method can be used not only to study the individual object, but also fit to statistical analysis for a sample.
Keywords:brain  tomography   emission-computed   single-photon
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