Application of a Deep Learning-Based Contrast-Boosting Algorithm to Low-Dose Computed Tomography Pulmonary Angiography With Reduced Iodine Load.

Journal: Journal of computer assisted tomography
PMID: 39438307

Abstract

OBJECTIVE: The aim of this study was to assess the effectiveness of a deep learning-based image contrast-boosting algorithm by enhancing the image quality of low-dose computed tomography pulmonary angiography at reduced iodine load.

Authors

  • Minsu Park
    School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Buk-gu, Gwangju, 61005, Republic of Korea.
  • Minhee Hwang
    Department of Radiology and Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan 49241, Korea.
  • Ji Won Lee
    Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan.
  • Kun-Il Kim
    Department of Radiology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan 50612, Korea.
  • Chulkyun Ahn
    Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea.
  • Young Ju Suh
    5 Department of Biomedical Sciences, School of Medicine, Inha University, Incheon, Republic of Korea.
  • Yeon Joo Jeong
    2 Department of Radiology, Pusan National University School of Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea.

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