Title
Cerebral Micro-Bleed Detection Based on the Convolution Neural Network With Rank Based Average Pooling.
Abstract
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%.
Year
DOI
Venue
2017
10.1109/ACCESS.2017.2736558
IEEE ACCESS
Keywords
Field
DocType
Convolutional neural network,cerebral micro-bleed,network structure,rank based average,pooling
Pattern recognition,Computer science,Convolutional neural network,Convolution,Pooling,Theoretical computer science,Artificial intelligence,Bleed,Distributed computing,Susceptibility weighted imaging,Hemosiderin
Journal
Volume
ISSN
Citations 
5
2169-3536
16
PageRank 
References 
Authors
0.67
10
5
Name
Order
Citations
PageRank
Shuihua Wang1156487.49
Yongyan Jiang2160.67
Xiao-Xia Hou3823.24
Hong Cheng470365.27
Sidan Du531431.20