Deep-Learning-Based MRI Microbleeds Detection for Cerebral Small Vessel Disease on Quantitative Susceptibility Mapping.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date: Dec 27, 2023

Abstract

BACKGROUND: Cerebral microbleeds (CMB) are indicators of severe cerebral small vessel disease (CSVD) that can be identified through hemosiderin-sensitive sequences in MRI. Specifically, quantitative susceptibility mapping (QSM) and deep learning were applied to detect CMBs in MRI.

Authors

  • Peng Xia
    State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P.R. China.
  • Edward S Hui
    Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China. Electronic address: edward.s.hui@gmail.com.
  • Bryan J Chua
    Division of Neurology, Department of Medicine, The University of Hong Kong, Hong Kong, China.
  • Fan Huang
  • Zuojun Wang
    Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China.
  • Huiqin Zhang
    Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China.
  • Han Yu
    1Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University, Singapore, 639798 Singapore.
  • Kui Kai Lau
    Division of Neurology, Department of Medicine, The University of Hong Kong, Hong Kong, China.
  • Henry K F Mak
    Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China.
  • Peng Cao
    Medical Image Computing Laboratory of Ministry of Education, Northeastern University, 110819, Shenyang, China.

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