Diagnostic performance of deep learning-based automatic white matter hyperintensity segmentation for classification of the Fazekas scale and differentiation of subcortical vascular dementia.

Abstract

Authors

• Leehi Joo
  Department of Radiology, Korea University Guro Hospital, Seoul, Republic of Korea.
• Woo Hyun Shim
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
• Chong Hyun Suh
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
• Su Jin Lim
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
• Hwon Heo
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
• Woo Seok Kim
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
• Eunpyeong Hong
  VUNO Inc., Seoul, Republic of Korea.
• Dongsoo Lee
  VUNO Inc., Seoul, Republic of Korea.
• Jinkyeong Sung
  From the R&D Center, VUNO, 507 Gangnamdae-ro, Seocho-gu, Seoul 06536, South Korea (J.S., W.B., B.P., E.J., K.H.J.); and Department of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea (S.P., S.M.L., J.B.S.).
• Jae-Sung Lim
  Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
• Jae-Hong Lee
  Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
• Sang Joon Kim
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.

Keywords

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