| 李淑宇,石峰,蒲放,蒋田仔,谢晟,王荫华.基于MRI海马形状特征的阿尔茨海默病的自动判别[J].中国医学影像技术,2006,22(9):1321~1324 |
| 基于MRI海马形状特征的阿尔茨海默病的自动判别 |
| Automatic discrimination of Alzheimer's disease from normal aging based on MRI hippocampal shape analysis |
| 投稿时间：2006-06-14 修订日期：2006-07-30 |
| DOI： |
| 中文关键词: 海马形状 磁共振成像 阿尔茨海默病 自动判别 |
| 英文关键词:Hippocampal shape Magnetic resonance imaging Alzheimer's disease Automatic discrimination |
| 基金项目:国家自然科学基金资助项目(60121302,10372065)。 |
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| 中文摘要: |
| 目的 通过海马的MRI影像学分析,研究阿尔茨海默病(AD)患者海马形状的局部异常模式,并构建最优的分类器函数辅助诊断AD。方法 对19例AD患者和20名正常老年对照者行MRI扫描,建立海马表面模型,测量海马表面的局部萎缩,构建分类器函数自动判别AD病。结果 自动判别的正确率,用留一法交叉验证实验的平均正确率分别为右海马82.1％,左海马92.3％;100次3重交叉验证实验的平均正确率为右海马82.5％,左海马87.2％。结论 利用MRI海马的形状特征自动判别AD是可行的。 |
| 英文摘要: |
| Objective Based on the MRI hippocampal shape analysis, to study the regional pattern differences between Alzheimer's disease (AD) and normal aging, and build effective classifiers to assist the diagnosis of AD. Methods Conventional MRI were performed in 19 AD patients and 20 age- and gender-matched healthy controls. Then hippocampal surface models were constructed and regional surface deformations were characterized by surface-based measures. Finally, effective classifiers were built to discriminate AD from normal aging. Results The accuracy of automatic recognition were 82.1% and 92.3% by using leave-one-out cross-validation, and similarly the average accuracy of randomized 3-fold cross-validation by 100 times were 82.5% and 87.2% resulted by right and left hippocampus respectively. Conclusion Hippocampal shape analysis is effective for the automatic recognition of AD. |
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