A deep learning algorithm may automate intracranial aneurysm detection on MR angiography with high diagnostic performance.

Journal: European radiology
Published Date: May 30, 2020

Abstract

OBJECTIVES: To develop a deep learning algorithm for automated detection and localization of intracranial aneurysms on time-of-flight MR angiography and evaluate its diagnostic performance.

Authors

  • Bio Joo
    Department of Radiology, Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
  • Sung Soo Ahn
    Department of Radiology, Severance Hospital, Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, Seoul, Korea. sungsoo@yuhs.ac.
  • Pyeong Ho Yoon
    Department of Radiology, National Health Insurance Service Ilsan Hospital, Goyang-si, Gyeonggi-do, Korea.
  • Sohi Bae
    Department of Radiology, National Health Insurance Service Ilsan Hospital, Goyang-si, Gyeonggi-do, Korea.
  • Beomseok Sohn
    Department of Radiology, Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
  • Yong Eun Lee
    DEEPNOID, Seoul, Korea.
  • Jun Ho Bae
    DEEPNOID, Seoul, Korea.
  • Moo Sung Park
    DEEPNOID, Seoul, Korea.
  • Hyun Seok Choi
    Department of Radiology, Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
  • Seung-Koo Lee
    Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea.

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