Deep learning-based image reconstruction improves radiologic evaluation of pituitary axis and cavernous sinus invasion in pituitary adenoma.

Abstract

Authors

• Hyeryeong Park
  University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Republic of Korea.
• Yeo Kyung Nam
  Department of Radiology and Research Institute of Radiology, Asan Medical Centre, University of Ulsan College of Medicine, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Republic of Korea.
• Ho Sung Kim
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
• Ji Eun Park
  Department of Anatomy and Cell Biology, College of Medicine, Dong-A University, Busan 602-714, Korea.
• Da Hyun Lee
  Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Korea.
• Joonsung Lee
  From the Department of Radiology and Research Institute of Radiology (M.K., H.S.K., H.J.K., J.E.P., S.J.K.), Department of Clinical Epidemiology and Biostatistics (S.Y.P.), and Department of Neurosurgery (Y.H.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-Gu, Seoul 05505, South Korea; GE Healthcare Korea, Seoul, Korea (J.L.); GE Healthcare Canada, Calgary, Canada (M.R.L.); and Department of Radiology, University of Calgary, Calgary, Canada (M.R.L.).
• Seonok Kim
  Department of Clinical Epidemiology and Biostatistics, Asan Medical Centre, University of Ulsan College of Medicine, Seoul, Republic of Korea.
• Young-Hoon Kim
  Department of Orthopedic Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.

Keywords

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