Impact of Deep Learning-based Optimization Algorithm on Image Quality of Low-dose Coronary CT Angiography with Noise Reduction: A Prospective Study.

Journal: Academic radiology
Published Date: Dec 19, 2019

Abstract

RATIONALE AND OBJECTIVES: To evaluate deep learning (DL)-based optimization algorithm for low-dose coronary CT angiography (CCTA) image noise reduction and image quality (IQ) improvement.

Authors

  • Peijun Liu
    Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
  • Man Wang
    Department of Forensic Science, Soochow University, Suzhou 215000, Jiangsu Province, China.
  • Yining Wang
    Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China.
  • Min Yu
    From the Division of Laboratory Medicine, Department of Pathology, University of Virginia School of Medicine and Health System, Charlottesville. Dr Yu is currently located in the Department of Pathology and Laboratory Medicine, University of Kentucky Medical Center, Lexington.
  • Yun Wang
    Department of Anesthesiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, People's Republic of China.
  • Zhuoheng Liu
    CT Business Unit, Neusoft Medical System Company, Shenyang, China.
  • Yumei Li
    Departments of Radiology, Peking Union Medical College Hospital, Beijing.
  • Zhengyu Jin
    Departments of Radiology, Peking Union Medical College Hospital, Beijing.

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