Comparison of a Deep Learning-Based Reconstruction Algorithm with Filtered Back Projection and Iterative Reconstruction Algorithms for Pediatric Abdominopelvic CT.

Journal: Korean journal of radiology
Published Date:

Abstract

OBJECTIVE: To compare a deep learning-based reconstruction (DLR) algorithm for pediatric abdominopelvic computed tomography (CT) with filtered back projection (FBP) and iterative reconstruction (IR) algorithms.

Authors

  • Wookon Son
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Minwoo Kim
    School of Electronics and Information Engineering, Korea Aerospace University, Goyang-si 10540, Korea. minwoo@kau.kr.
  • Jae-Yeon Hwang
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Yong-Woo Kim
    Department of Orthopedic Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
  • Chankue Park
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Ki Seok Choo
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea. kschoo0618@naver.com.
  • Tae Un Kim
    Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Joo Yeon Jang
    Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.