Detection of cerebral microbleeding based on deep convolutional neural network

Siyuan Lu, Zhihai Lu, Xiaoxia Hou, Hong Cheng, Shuihua Wang

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

9 Citations (Scopus)

Abstract

Background and Objective Cerebral microbleeding (CMB) is associated with many brain diseases, such as dementia and vascular disease. CMBs can be detected by brain magnetic resonance imaging (MRI). Susceptibility weighted imaging (SWI) is commonly employed since it can give better sensitivity than standard MRI. However, CMBs are usually small and they can be distributed throughout brain, manual analysis is arduous and tedious. We proposed to use deep learning methods to detect CMBs. First, we collected 64 brain SWI. We used a sliding window size of 61×61 pixel to generate 10000 samples. Then, we labeled the samples as non-CMB or CMB manually. Finally, we employed convolutional neural network (CNN) for classification. Results In the experiment, we used 8000 samples to train the CNN, the rest 2000 for testing. The proposed method yielded a sensitivity of 97.29%, a specificity of92.23%, and an overall accuracy of 96.05%. Conclusions The results suggested our method can detect and locate CMBs automatically and accurately.

Original languageEnglish
Title of host publication2016 13th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages93-96
Number of pages4
ISBN (Electronic)9781509061259
DOIs
Publication statusPublished - 20 Oct 2017
Externally publishedYes
Event14th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2017 - Chengdu, Sichuan Province, China
Duration: 15 Dec 201717 Dec 2017

Publication series

Name2016 13th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2017
Volume2018-February

Conference

Conference14th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2017
Country/TerritoryChina
CityChengdu, Sichuan Province
Period15/12/1717/12/17

Keywords

  • Cerebral microbleeding
  • Computer-aided Diagnosis
  • Convolutional Neural Network
  • Deep Learning
  • Machine Learning

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