Novel Approaches to Detection of Cerebral Microbleeds: Single Deep Learning Model to Achieve a Balanced Performance.

Journal: Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Published Date: Jun 25, 2021

Abstract

PURPOSE: Cerebral microbleeds (CMBs) are considered essential indicators for the diagnosis of cerebrovascular disease and cognitive disorders. Traditionally, CMBs are manually interpreted based on criteria including the shape, diameter, and signal characteristics after an MR examination, such as susceptibility-weighted imaging or gradient echo imaging (GRE). In this paper, an efficient method for CMB detection in GRE scans is presented.

Authors

  • Min Jae Myung
    Department of Radiology, Kyung Hee University College of Medicine, Kyung Hee University Hospital, #23 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea. Electronic address: bandilee@khu.ac.kr.
  • Kyung Mi Lee
    Department of Radiology, Kyung Hee University College of Medicine, Kyung Hee University Hospital, #23 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.
  • Hyug-Gi Kim
    Department of Biomedical Engineering, Graduate School, Kyung Hee University, 1732, Deogyeong-daero, Giheunggu, Yongin-si, Gyeonggi-do 446-701, Korea.
  • Janghoon Oh
    Department of Biomedical Science and Technology, Graduate School, Kyung Hee University, #23 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.
  • Ji Young Lee
  • Ilah Shin
    Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, Seoul, Republic of Korea.
  • Eui Jong Kim
    Department of Radiology, Kyung Hee University Hospital, Seoul, Korea.
  • Jin San Lee
    Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.

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