Automated method for identification of patients with Alzheimer's disease based on three-dimensional MR images
Automated method for identification of patients with Alzheimer's disease based on three-dimensional MR images
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DOI：
10.1016/j.acra.2007.10.020
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发表时间：
2008-03-01
影响因子：
4.8
通讯作者：
Higashida, Yoshiharu
中科院分区：
文献类型：
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作者：
Arimura, Hidetaka;Yoshiura, Takashi;Higashida, Yoshiharu
理由和目标。基于三维（313）TI加权磁共振（MR）图像，开发了一种自动识别阿尔茨海默病（AD）所致脑萎缩患者的方法。我们提出的方法包括确定萎缩的图像特征和识别AD患者。萎缩图像特征包括白色物质和灰质体积、脑脊液（CSF）体积和基于水平集方法确定的大脑皮质厚度。皮质厚度的测量与正常矢量的体素的基础上，这是通过区分水平集函数。通过将大脑紧紧包裹在水平集方法确定的传播表面中来提取脑沟和侧脑室（LV）内的CSF空间。AD病例的识别使用支持向量机（SVM）分类器进行，该分类器由AD和非AD病例的萎缩图像特征进行训练，然后基于SVM模型将未知病例分类为AD或非AD组。我们将我们提出的方法应用于54例患者的全脑MR图像，其中包括29例临床诊断的AD患者（年龄范围，52-82岁;平均年龄，70岁）和25例非AD患者（年龄范围，49-78岁;平均年龄，62岁）。结果表明，在54例AD患者中，采用计算机辅助的方法得到的受试者工作特征（ROC）曲线下面积（Az值）为0.909。这一初步结果表明，我们的方法可能是有前途的检测AD患者。
Rationale and Objectives. An automated method for identification of patients with cerebral atrophy due to Alzheimer's disease (AD) was developed based on three-dimensional (313) TI-weighted magnetic resonance (MR) images.Materials and Methods. Our proposed method consisted of determination of atrophic image features and identification of AD patients. The atrophic image features included white matter and gray matter volumes, cerebrospinal fluid (CSF) volume, and cerebral cortical thickness determined based on a level set method. The cortical thickness was measured with normal vectors on a voxel-by-voxel basis, which were determined by differentiating a level set function. The CSF spaces within cerebral sulci and lateral ventricles (LVs) were extracted by wrapping the brain tightly in a propagating surface determined with a level set method. Identification of AD cases was performed using a support vector machine (SVM) classifier, which was trained by the atrophic image features of AD and non-AD cases, and then an unknown case was classified into either AD or non-AD group based on an SVM model. We applied our proposed method to MR images of the whole brains obtained from 54 cases, including 29 clinically diagnosed AD cases (age range, 52-82 years; mean age, 70 years) and 25 non-AD cases (age range, 49-78 years; mean age, 62 years).Results. As a result, the area under a receiver operating characteristic (ROC) curve (Az value) obtained by our computerized method was 0.909 based on a leave-one-out test in identification of AD cases among 54 cases.Conclusion. This preliminary result showed that our method may be promising for detecting AD patients.