Improving radiomics reproducibility using deep learning-based image conversion of CT reconstruction algorithms in hepatocellular carcinoma patients.

Journal: European radiology
Published Date: Sep 1, 2023

Abstract

OBJECTIVES: CT reconstruction algorithms affect radiomics reproducibility. In this study, we evaluate the effect of deep learning-based image conversion on CT reconstruction algorithms.

Authors

  • Heejin Lee
    Department of Applied bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea.
  • Won Chang
  • Hae Young Kim
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Pamela Sung
    Department of Radiology, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Republic of Korea.
  • Jungheum Cho
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.
  • Yoon Jin Lee
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea.
  • Young Hoon Kim
    Department of Surgery, College of Medicine, Ulsan University, Asan Medical Center, Seoul, Korea.

Keywords

External Resources

Popular Topics
Recent Journals