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

• Main Authors: Shuihua Wang, Yongyan Jiang, Xiaoxia Hou, Hong Cheng, Sidan Du
• Format: Article
• Language: English
• Published: IEEE 2017-01-01
• Series: IEEE Access
• Subjects: Convolutional neural network; cerebral micro-bleed; network structure; rank based average pooling
• Online Access: https://ieeexplore.ieee.org/document/8013653/
• ISSN: 2169-3536

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%.