Development and Validation of a Deep Learning-Based Synthetic Bone-Suppressed Model for Pulmonary Nodule Detection in Chest Radiographs.

Abstract

Authors

• Hwiyoung Kim
  Department of Radiological Science, Yonsei University College of Medicine, Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea. Electronic address: HYKIM82@yuhs.ac.
• Kye Ho Lee
  Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
• Kyunghwa Han
  From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea (S.H.P.); and Department of Radiology, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea (K.H.).
• Ji Won Lee
  Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan.
• Jin Young Kim
  Department of Orthopaedic Surgery, Dongguk University Ilsan Hospital, Goyang, Korea.
• Dong Jin Im
  Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
• Yoo Jin Hong
  Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
• Byoung Wook Choi
• Jin Hur
  Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.

Keywords

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