Houston A S, Kemp P M, Macleod M A
Department of Nuclear Medicine, Royal Naval Hospital, Haslar, Gosport, United Kingdom.
J Nucl Med. 1994 Feb;35(2):239-44.
A normal atlas for HMPAO rCBF SPECT images was obtained from images of 53 normal controls. Following image registration and normalization, a mean image was extracted, while images representing correlated normal deviants were identified using principal component analysis. These images formed the "building blocks" of the atlas. For subsequent images, the atlas was used to create a "nearest normal equivalent" image, which was compared to a residual standard deviation image to determine the significance of deviations in the new image.
Images from 30 patients (10 with Alzheimer's disease; 12 with single or multiple infarcts; and 8 normals) were analyzed.
Using an optimal decision level, 10/10 patients with Alzheimer's disease and 11/12 patients with infarcts were correctly identified, with only one false-positive resulting. We utilized a database of images obtained from normal controls to create a normal atlas.
从53名正常对照者的图像中获取HMPAO rCBF SPECT图像的正常图谱。经过图像配准和归一化后，提取平均图像，同时使用主成分分析识别代表相关正常偏差的图像。这些图像构成了图谱的“构建模块”。对于后续图像，使用该图谱创建“最接近正常等效”图像，并将其与残余标准差图像进行比较，以确定新图像中偏差的显著性。
分析了30名患者的图像（10名患有阿尔茨海默病；12名患有单发或多发梗死；8名正常）。
使用最佳决策水平，10名阿尔茨海默病患者中的10名和12名梗死患者中的11名被正确识别，仅产生1例假阳性。我们利用从正常对照者获得的图像数据库创建了一个正常图谱。
