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Deep Learning for Cerebral Microbleed Identification

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Pathological Brain Detection

Part of the book series: Brain Informatics and Health ((BIH))

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Abstract

Cerebral microbleeds (CMBs) are the small foci of chronic blood products. CMBs are closely related to many diseases such as dementia, siderosis, ageing, etc. A data balance method is used for their identification, since CMB voxels in collected brain images are usually about 2000 times less common than non-CMB voxels.

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Authors and Affiliations

  1. School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, Henan, China

    Shui-Hua Wang & Yu-Dong Zhang

  2. School of Electronics Science and Engineering, Nanjing University, Nanjing, Jiangsu, China

    Shui-Hua Wang

  3. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

  4. Translational Imaging Division & MRI Unit, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA

    Zhengchao Dong

  5. Shepherd University, Shepherdstown, WV, USA

    Preetha Phillips

  6. West Virginia School of Osteopathic Medicine, St. Lewisburg, WV, USA

    Preetha Phillips

Authors
  1. Shui-Hua Wang
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  2. Yu-Dong Zhang
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  3. Zhengchao Dong
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  4. Preetha Phillips
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Wang, SH., Zhang, YD., Dong, Z., Phillips, P. (2018). Deep Learning for Cerebral Microbleed Identification. In: Pathological Brain Detection. Brain Informatics and Health. Springer, Singapore. https://doi.org/10.1007/978-981-10-4026-9_11

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  • DOI: https://doi.org/10.1007/978-981-10-4026-9_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4025-2

  • Online ISBN: 978-981-10-4026-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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