End-to-End Deep Learning-Based Motion Correction and Reconstruction for Accelerated Whole-Heart Joint T/T Mapping.

Journal: Magnetic resonance imaging
Published Date: Apr 21, 2025

Abstract

PURPOSE: To accelerate 3D whole-heart joint T/T mapping for myocardial tissue characterization using an end-to-end deep learning algorithm for joint motion estimation and model-based motion-corrected reconstruction of multi-contrast undersampled data.

Authors

  • Lina Felsner
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
  • Carlos Velasco
    School of Biomedical Engineering and Imaging Science, King's College London, London, United Kingdom.
  • Andrew Phair
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
  • Thomas J Fletcher
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
  • Haikun Qi
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, London, United Kingdom.
  • René M Botnar
    School of Biomedical Engineering and Imaging Sciences, King's College London, UK; Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Claudia Prieto
    School of Biomedical Engineering & Imaging Sciences, King's College, London, UK.

Keywords

External Resources

Popular Topics
Recent Journals