Automatic Cerebral Microbleeds Detection from MR Images via Independent Subspace Analysis Based Hierarchical Features
Refereed conference paper presented and published in conference proceedings


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摘要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.
著者Dou Q, Chen H, Yu LQ, Shi L, Wang DF, Mok VCT, Heng PA
會議名稱37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
會議開始日25.08.2015
會議完結日29.08.2015
會議地點Milan
會議國家/地區意大利
期刊名稱Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society
出版年份2015
月份1
日期1
出版社IEEE
頁次7933 - 7936
電子國際標準書號978-1-4244-9270-1
國際標準期刊號1557-170X
語言英式英語
關鍵詞brain SWI; Cerebral microbleed; computer aided diagnosis; feature representation

上次更新時間 2020-18-11 於 01:10