A deep learning-based automatic system for intracranial aneurysms diagnosis on three-dimensional digital subtraction angiographic images.

Journal: Medical physics
Published Date: Jul 15, 2022

Abstract

BACKGROUND: Intracranial aneurysms (IAs) are a life-threatening disease. Their rupture can lead to hemorrhagic stroke. Most studies applying deep learning for the detection of aneurysms are based on angiographic images. However, critical diagnostic information such as morphology and aneurysm location are not captured by deep learning algorithms and still require manual assessments.

Authors

  • Chubin Ou
    Faculty of Medicine and Health, Macquarie University, 75 Talavera Road, Sydney, Australia.
  • Yi Qian
    Jinhua People's Hospital, Jinhua, China. qianyicosta@163.com.
  • Winston Chong
    Monash Imaging and Department of Surgery, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia.
  • Xiaoxi Hou
    Faculty of Medicine and Health, Macquarie University, 75 Talavera Road, Sydney, Australia.
  • Mingzi Zhang
    Institute of Fluid Science, Tohoku University, 2-1-1, Katahira, Aoba-ku, Sendai, Miyagi, 980-8577, Japan.
  • Xin Zhang
    First Department of Infectious Diseases, The First Affiliated Hospital of China Medical University, Shenyang, China.
  • Weixin Si
    Guangdong Provincial Key Laboratory of Machine Vision and Virtual Reality Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
  • Chuan-Zhi Duan
    Neurosurgery Center, Department of Cerebrovascular Surgery, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, The Neurosurgery Institute of Guangdong Province, Zhujiang Hospital, Southern Medical University, Guangzhou, China.

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