CT iterative vs deep learning reconstruction: comparison of noise and sharpness.

Journal: European radiology
Published Date: Oct 15, 2020

Abstract

OBJECTIVES: To compare image noise and sharpness of vessels, liver, and muscle in lower extremity CT angiography between "adaptive statistical iterative reconstruction-V" (ASIR-V) and deep learning reconstruction "TrueFidelity" (TFI).

Authors

  • 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.
  • Yunsub Jung
    CT Research Team, GE Healthcare Korea, Seoul, Korea.
  • Hee Seok Jeong
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Jae-Yeon Hwang
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Mi Sook Yun
    Division of Biostatistics, Pusan National University Yangsan Hospital, Yangsan, Korea.

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