Automated detection of intracranial artery stenosis and occlusion in magnetic resonance angiography: A preliminary study based on deep learning.

Journal: Magnetic resonance imaging
PMID:

Abstract

BACKGROUND AND OBJECTIVES: Intracranial atherosclerotic stenosis of a major intracranial artery is the common cause of ischemic stroke. We evaluate the feasibility of using deep learning to automatically detect intracranial arterial steno-occlusive lesions from time-of-flight magnetic resonance angiography.

Authors

  • Jinming Qiu
    Department of Radiology, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong, PR China; Department of Radiology, the Sixth Affiliated Hospital, South China University of Technology, Foshan 528000, Guangdong, PR China.
  • Guanru Tan
    Department of Computer Science, Shantou University, Shantou 515041, Guangdong, PR China.
  • Yan Lin
  • Jitian Guan
    Department of Radiology, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong, PR China.
  • Zhuozhi Dai
    Department of Radiology, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong, PR China.
  • Fei Wang
    Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States.
  • Caiyu Zhuang
    Department of Radiology, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong, PR China.
  • Alan H Wilman
    Department of Biomedical Engineering, University of Alberta, Edmonton, Canada.
  • Huaidong Huang
    Department of Radiology, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong, PR China.
  • Zhen Cao
  • Yanyan Tang
    Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, China.
  • Yanlong Jia
    Department of Radiology, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong, PR China.
  • Yan Li
    Interdisciplinary Research Center for Biology and Chemistry, Liaoning Normal University, Dalian, China.
  • Teng Zhou
    School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China.
  • Renhua Wu
    Department of Medical Imaging, The 2nd Affiliated Hospital, Shantou University Medical College, Shantou 515041, China.