Deep Learning Image Reconstruction for Transcatheter Aortic Valve Implantation Planning: Image Quality, Diagnostic Performance, Contrast volume and Radiation Dose Assessment.

Journal: Academic radiology
Published Date: Mar 11, 2024

Abstract

RATIONALE AND OBJECTIVES: To assess image quality, contrast volume and radiation dose reduction potential and diagnostic performance with the use of high-strength deep learning image reconstruction (DLIR-H) in transcatheter aortic valve implantation (TAVI) planning CT.

Authors

  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Zixuan Liu
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA.
  • Yong Cheng
    Department of Urology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
  • Ziwei Wang
    School of Information Technology and Electrical Engineering, University of Queensland, Brisbane Australia.
  • Zhenlin Li
    Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, P.R.China.
  • Jianying Li
    CT Research Center, GE Healthcare China, Beijing 100176, China.
  • Tao Shuai
    Department of Radiology, West China Hospital of Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.

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