Prediction and classification of Alzheimer disease based on quantification of MRI deformation.
文献类型：期刊论文
| 作者 | Long, Xiaojing; Chen, Lifang; Jiang, Chunxiang; Zhang, Lijuan |
| 刊名 | PLOS ONE
 |
| 出版日期 | 2017 |
| 文献子类 | 期刊论文 |
| 英文摘要 | Detecting early morphological changes in the brain and making early diagnosis are important for Alzheimer's disease (AD). High resolution magnetic resonance imaging can be used to help diagnosis and prediction of the disease. In this paper, we proposed a machine learning method to discriminate patients with AD or mild cognitive impairment (MCI) from healthy elderly and to predict the AD conversion in MCI patients by computing and analyzing the regional morphological differences of brain between groups. Distance between each pair of subjects was quantified from a symmetric diffeomorphic registration, followed by an embedding algorithm and a learning approach for classification. The proposed method obtained accuracy of 96.5% in differentiating mild AD from healthy elderly with the whole-brain gray matter or temporal lobe as region of interest (ROI), 91.74% in differentiating progressive MCI from healthy elderly and 88.99% in classifying progressive MCI versus stable MCI with amygdala or hippocampus as ROI. This deformation-based method has made full use of the pair-wise macroscopic shape difference between groups and consequently increased the power for discrimination. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/12047]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 作者单位 | PLOS ONE |
| 推荐引用方式 GB/T 7714 | Long, Xiaojing,Chen, Lifang,Jiang, Chunxiang,et al. Prediction and classification of Alzheimer disease based on quantification of MRI deformation.[J]. PLOS ONE,2017. |
| APA | Long, Xiaojing,Chen, Lifang,Jiang, Chunxiang,&Zhang, Lijuan.(2017).Prediction and classification of Alzheimer disease based on quantification of MRI deformation..PLOS ONE. |
| MLA | Long, Xiaojing,et al."Prediction and classification of Alzheimer disease based on quantification of MRI deformation.".PLOS ONE (2017). |
入库方式： OAI收割
来源：深圳先进技术研究院
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