Implementation and prospective clinical validation of AI-based planning and shimming techniques in cardiac MRI.

Journal: Medical physics
Published Date: Nov 23, 2021

Abstract

PURPOSE: Cardiovascular magnetic resonance (CMR) is a vital diagnostic tool in the management of cardiovascular diseases. The advent of advanced CMR technologies combined with artificial intelligence (AI) has the potential to simplify imaging, reduce image acquisition time without compromising image quality (IQ), and improve magnetic field uniformity. Here, we aim to implement two AI-based deep learning techniques for automatic slice alignment and cardiac shimming and evaluate their performance in clinical cardiac magnetic resonance imaging (MRI).

Authors

  • Masoud Edalati
    United Imaging Healthcare America, Inc., Houston, Texas, USA.
  • Yuan Zheng
    School of Finance, Anhui University of Finance and Economics, Bengbu, Anhui 233030, China.
  • Mary P Watkins
    Cardiology Division, Washington University School of Medicine, St. Louis, Missouri, USA.
  • Junjie Chen
    College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China.
  • Liu Liu
    Department of Oral and Maxillofacial Radiology, School of Dentistry, Dental Science Research Institute, Chonnam National University, Gwangju, South Korea.
  • Shuheng Zhang
    United Imaging Healthcare America, Inc., Houston, Texas, USA.
  • Yanli Song
    United Imaging Healthcare America, Inc., Houston, Texas, USA.
  • Samira Soleymani
    Department of Statistical and Actuarial Sciences, University of Western Ontario, London, Ontario, Canada.
  • Daniel J Lenihan
    Cardiology Division, Washington University School of Medicine, St. Louis, Missouri, USA.
  • Gregory M Lanza
    Cardiology Division, Washington University School of Medicine, St. Louis, Missouri, USA.

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