CASIA OpenIR  > 中国科学院分子影像重点实验室
Classification of brain disease from magnetic resonance images based on multi-level brain partitions
Li T(李涛); Wensheng Zhang
2017
会议名称IEEE Engineering in Medicine and Biology Society
会议录名称Biomedical Imaging & Image Processing
会议日期August 16-20, 2016
会议地点Orlando, Florida, USA
摘要
In this paper, we present a classification method based on the multi-level brain partitions. Bag-of-visual-words model is used. Firstly, the representative SIFT features are extracted from brain template as the basic visual words. Secondly, individual MR images are described using the basic visual words and support vector machine classifiers are trained for different brain partitions respectively. Thirdly, the final classification is derived from the combination of multiple classifiers. We apply this method to MR images of Alzheimer's disease and Parkinson's disease. The results demonstrate that the multi-level partitions favors the classification accuracy of brain disease from MR images.
 
关键词Brain Disease Classification
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12807
专题中国科学院分子影像重点实验室
通讯作者Wensheng Zhang
作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Li T,Wensheng Zhang. Classification of brain disease from magnetic resonance images based on multi-level brain partitions[C],2017.
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