Cerebral Micro-Bleed Detection Based on the Convolution Neural Network With Rank Based Average Pooling

被引：76

作者：

Wang, Shuihua ^{[1
]}

Jiang, Yongyan ^{[2
]}

Hou, Xiaoxia ^{[3
]}

Cheng, Hong ^{[3
]}

Dui, Sidan ^{[1
]}

机构：

[1] Nanjing Univ, Sch Elect Engn, Nanjing 210046, Jiangsu, Peoples R China

[2] Zhongyuan Univ Technol, Coll Sci, Zhengzhou 450007, Henan, Peoples R China

[3] Nanjing Med Univ, Dept Neurol, Affiliated Hosp 1, Nanjing 210029, Jiangsu, Peoples R China

来源：

IEEE ACCESS | 2017年 / 5卷

关键词：

Convolutional neural network; cerebral micro-bleed; network structure; rank based average; pooling; COMPUTER-AIDED DETECTION; MICROBLEEDS;

D O I：

10.1109/ACCESS.2017.2736558

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Cerebral micro-bleed (CMB) is small perivascular hemosiderin deposits from leakage through cerebral small vessels. They can result from cerebra-vascular disease, dementia, or simply from normal aging. It can be visualized via the susceptibility weighted imaging (SWI). Based on the SWI, we propose to use different structures of the CNN with rank-based average pooling to detect the CMB, and compare this method used in this paper to the current state-of-the-art methods. We can find that the CNN with five layers obtains the best performance, with a sensitivity of 96.94%, a specificity of 97.18%, and an accuracy of 97.18%.

引用

页码：16576 / 16583

页数：8

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