Automatic Cerebral Microbleeds Detection from MR Images via Independent Subspace Analysis Based Hierarchical Features

作者：Dou Qi^*; Chen Hao; Yu Lequan; Shi Lin; Wang Defeng; Mok Vincent C T; Heng Pheng Ann

来源：37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015-08-25 to 2015-08-29.

• Cerebral microbleed
• brain SWI
• feature representation
• computer aided diagnosis

With the development of susceptibility weighted imaging (SWI) technology, cerebral microbleed (CMB) detection is increasingly essential in cerebrovascular diseases diagnosis and cognitive impairment assessment. Clinical CMB detection is based on manual rating which is subjective and time-consuming with limited reproducibility. In this paper, we propose a computer-aided system for automatic detection of CMBs from brain SWI images. Our approach detects the CMBs within three stages: (i) candidates screening based on intensity values (ii) compact 3D hierarchical features extraction via a stacked convolutional Independent Subspace Analysis (ISA) network (iii) false positive candidates removal with a support vector machine (SVM) classifier based on the learned representation features from ISA. Experimental results on 19 subjects (161 CMBs) achieve a high sensitivity of 89.44% with an average of 7.7 and 0.9 false positives per subject and per CMB, respectively, which validate the efficacy of our approach.

• 出版日期2015
• 单位浙江大学; 香港中文大学; 香港大学