Deep learning for automated cerebral aneurysm detection on computed tomography images.

Journal: International journal of computer assisted radiology and surgery
Published Date: Feb 13, 2020

Abstract

PURPOSE: Cerebrovascular aneurysms are being observed with rapidly increasing incidence. Therefore, tools are needed for accurate and efficient detection of aneurysms. We used deep learning techniques with CT angiography acquired from multiple medical centers and different machines to develop and evaluate an automatic detection model.

Authors

  • Xilei Dai
    Faculty of Medicine and Health, Macquarie University, 75 Talavera Road, Sydney, Australia.
  • Lixiang Huang
    Department of Radiology, Tianjin First Central Hospital, Tianjin, 300192, China.
  • Yi Qian
    Jinhua People's Hospital, Jinhua, China. qianyicosta@163.com.
  • Shuang Xia
    Department of Radiology, Tianjin First Central Hospital, Tianjin, China.
  • Winston Chong
    Monash Imaging and Department of Surgery, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia.
  • Junjie Liu
    Tianjin Key Lab of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, 300072, China.
  • Antonio Di Ieva
    Neurosurgery Unit, Department of Clinical Medicine, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia.
  • Xiaoxi Hou
    Faculty of Medicine and Health, Macquarie University, 75 Talavera Road, Sydney, Australia.
  • Chubin Ou
    Faculty of Medicine and Health, Macquarie University, 75 Talavera Road, Sydney, Australia.

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