A Robust Deep Learning Segmentation Method for Hematoma Volumetric Detection in Intracerebral Hemorrhage.

Journal: Stroke
Published Date: Jan 1, 2022

Abstract

BACKGROUND AND PURPOSE: Hematoma volume (HV) is a significant diagnosis for determining the clinical stage and therapeutic approach for intracerebral hemorrhage (ICH). The aim of this study is to develop a robust deep learning segmentation method for the fast and accurate HV analysis using computed tomography.

Authors

  • Nannan Yu
    Department of Artificial Intelligence, School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou, China (N.Y., H.Y.).
  • He Yu
    Dept of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
  • Haonan Li
    Department of Biotechnology, College of Basic Medical Sciences, Dalian Medical University, China (H.L., J.W.).
  • Nannan Ma
    Radiology Department, Xuzhou Central Hospital, China (N.M., C.H.).
  • Chunai Hu
    Radiology Department, Xuzhou Central Hospital, China (N.M., C.H.).
  • Jia Wang
    Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun, Jilin, China.

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