Application of deep learning and radiomics in the prediction of hematoma expansion in intracerebral hemorrhage: a fully automated hybrid approach.

Journal: Diagnostic and interventional radiology (Ankara, Turkey)
PMID: 38654561

Abstract

PURPOSE: Spontaneous intracerebral hemorrhage (ICH) is the most severe form of stroke. The timely assessment of early hematoma enlargement and its proper treatment are of great significance in curbing the deterioration and improving the prognosis of patients with ICH. This study aimed to develop an automated hybrid approach to predict hematoma expansion in ICH.

Authors

  • Mengtian Lu
    The First Affiliated Hospital of Hubei University of Science and Technology, Xianning Central Hospital, Department of Radiology, Xianning, China
  • Yaqi Wang
    Key Laboratory of RF Circuits and Systems, Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Jiaqiang Tian
    The First Affiliated Hospital of Hubei University of Science and Technology, Xianning Central Hospital, Department of Radiology, Xianning, China
  • Haifeng Feng
    State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China; Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, 110169, China; University of Chinese Academy of Sciences, Beijing, 100049, China. Electronic address: fenghaifeng@sia.cn.

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