Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To evaluate the performance of a novel three-dimensional (3D) joint convolutional and recurrent neural network (CNN-RNN) for the detection of intracranial hemorrhage (ICH) and its five subtypes (cerebral parenchymal, intraventricular, subdural, epidural, and subarachnoid) in non-contrast head CT.

Authors

  • Hai Ye
    Department of Radiology, Shenzhen Second People's Hospital, Shenzhen Second Hospital Clinical Medicine College of Anhui Medical University, Shenzhen, China.
  • Feng Gao
    Department of Statistics, UCLA, Los Angeles, CA 90095, USA.
  • Youbing Yin
    Department of Engineering, CuraCloud Corporation, Seattle, WA, USA.
  • Danfeng Guo
  • Pengfei Zhao
    Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
  • Yi Lu
    Department of Gastrointestinal Endoscopy, The Sixth Affiliated Hospital, Sun Yat-Sen University, 26th Yuancun the Second Road, Guangzhou, 510655, Guangdong Province, China.
  • Xin Wang
    Key Laboratory of Bio-based Material Science & Technology (Northeast Forestry University), Ministry of Education, Harbin 150040, China.
  • Junjie Bai
    Department of Engineering, CuraCloud Corporation, Seattle, WA, USA.
  • Kunlin Cao
    Department of Engineering, CuraCloud Corporation, Seattle, WA, USA.
  • Qi Song
    ‡ College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
  • Heye Zhang
    School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China.
  • Wei Chen
    Department of Urology, Zigong Fourth People's Hospital, Sichuan, China.
  • Xuejun Guo
    Department of Respiratory Medicine, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China. guoxuejun@xinhuamed.com.cn.
  • Jun Xia
    Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China. xiajun2003sz@aliyun.com.