Diffusion-based image translation model from low-dose chest CT to calcium scoring CT with random point sampling.

Journal: Computers in biology and medicine
Published Date: Jun 7, 2025

Abstract

BACKGROUND: Coronary artery calcium (CAC) scoring is an important method for cardiovascular risk assessment. While artificial intelligence (AI) has been applied to automate CAC scoring in calcium scoring computed tomography (CSCT), its application to low-dose computed tomography (LDCT) scans, typically used for lung cancer screening, remains challenging due to the lower image quality and higher noise levels of LDCT.

Authors

  • Ji-Hoon Jung
    Biomedical Engineering Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, South Korea; Department of Biomedical Engineering, AMIST, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
  • Jong Eun Lee
    Department of Radiology, Chonnam National University Hospital, Gwangju, Republic of Korea.
  • Hyun Seo Lee
    Department of Biomedical Engineering, AMIST, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea; Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
  • Dong Hyun Yang
    Department of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
  • June-Goo Lee
    Biomedical Engineering Research Center, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea.

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