Automated Detection of Cerebral Microbleeds on Two-dimensional Gradient-recalled Echo T2* Weighted Images Using a Morphology Filter Bank and Convolutional Neural Network.

Journal: Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Published Date: Mar 15, 2024

Abstract

PURPOSE: We present a novel algorithm for the automated detection of cerebral microbleeds (CMBs) on 2D gradient-recalled echo T2* weighted images (T2*WIs). This approach combines a morphology filter bank with a convolutional neural network (CNN) to improve the efficiency of CMB detection. A technical evaluation was performed to ascertain the algorithm's accuracy.

Authors

  • Noriko Nishioka
    Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.
  • Yukie Shimizu
    Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, N14 W5, Kita-Ku, Sapporo, 060-8638, Japan.
  • Toru Shirai
    FUJIFILM Corporation, Medical Systems Research & Development Center.
  • Hisaaki Ochi
    Medical Systems Research & Development Center, FUJIFILM Corporation, Tokyo, Japan.
  • Yoshitaka Bito
    FUJIFILM Healthcare Corporation, Tokyo, Japan.
  • Kiichi Watanabe
    Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.
  • Hiroyuki Kameda
    School of Computer Science, Tokyo University of Technology, 1401-1 Katakura-machi, Hachioji-shi, Tokyo 192-0982, Japan.
  • Taisuke Harada
    Department of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, N15 W7, Kita-Ku, Sapporo, Hokkaido, 060-8638, Japan.
  • Kohsuke Kudo
    Departments of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, kita 15, nishi 7, kita-ku, Sapporo, Hokkaido, 060-8638, Japan.

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