Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.

Journal: Korean journal of radiology
Published Date: Sep 29, 2022

Abstract

OBJECTIVE: This study aimed to investigate whether a deep learning reconstruction (DLR) method improves the image quality, stent evaluation, and visibility of the valve apparatus in coronary computed tomography angiography (CCTA) when compared with filtered back projection (FBP) and hybrid iterative reconstruction (IR) methods.

Authors

  • Chuluunbaatar Otgonbaatar
    Department of Radiology, College of Medicine, Seoul National University, 03080 Seoul, Republic of Korea.
  • Jae-Kyun Ryu
    Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea.
  • Jaemin Shin
    Department of Neurology, 58934Korea University Guro Hospital, Seoul, Republic of Korea.
  • Ji Young Woo
    Department of Radiology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea.
  • Jung Wook Seo
    Department of Radiology, Inje University Ilsan Paik Hospital, 10380 Goyang, Republic of Korea.
  • Hackjoon Shim
    Connect AI Research Center, Yonsei University College of Medicine, 03772 Seoul, Republic of Korea.
  • Dae Hyun Hwang
    Department of Radiology, Inje University Seoul Paik Hospital, 04551 Seoul, Republic of Korea.

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