A deep-learning reconstruction algorithm that improves the image quality of low-tube-voltage coronary CT angiography.

Journal: European journal of radiology
Published Date:

Abstract

PURPOSE: To assess the image quality (IQ) of low tube voltage coronary CT angiography (CCTA) images reconstructed with deep learning image reconstruction (DLIR).

Authors

  • Mengzhen Wang
    Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China.
  • Jing Fan
  • Xiaofeng Shi
    Department of Infectious Diseases, Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Le Qin
    Ocean College, Zhoushan Campus, Zhejiang University, Zhoushan, China.
  • Fuhua Yan
    Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China. Electronic address: yfh11655@rjh.com.cn.
  • Wenjie Yang
    Department of Radiology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China. lisa_ywj@163.com.