Motion-Guided Physics-Based Learning for Cardiac MRI Reconstruction

Hammernik K, Pan J, Rueckert D, Kustner T (2021)

Publication Type: Conference contribution

Publication year: 2021

Journal

Conference Record of the Asilomar Conference on Signals, Systems and Computers Institute of Electrical and Electronics Engineers

Publisher: IEEE Computer Society

Book Volume: 2021-October

Pages Range: 900-907

Conference Proceedings Title: Conference Record - Asilomar Conference on Signals, Systems and Computers

Event location: Virtual, Pacific Grove, CA, USA

ISBN: 9781665458283

DOI: 10.1109/IEEECONF53345.2021.9723134

Abstract

In this work, we propose a robust learning-based cardiac motion estimation framework, to estimate non-rigid cardiac motion fields from undersampled cardiac data. Our proposed frameworks leverages the advantages of a lightweight motion estimation network and a combination of photometric and smoothness losses. This framework enables the prediction of cardiac motion fields to further improve on the downstream task of motion-compensated image reconstruction. We evaluate our motion estimation framework qualitatively and quantitatively on 41 in-house acquired 2D cardiac CINE MRIs. Our proposed method provides quantitatively competitive results to state-of-the art methods in motion estimation, and superior results in image reconstruction in terms of structural similarity metric and peak-signal-to-noise ratio. Furthermore, our frameworks allows for ~3500x faster motion estimation compared to state-of-the-art approaches, opening up the practical application potential for motion-guided physics-based image reconstruction.

Involved external institutions

Technische Universität München (TUM) DE Germany (DE) Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB) Universitätsklinikum Tübingen DE Germany (DE)

How to cite

APA:

Hammernik, K., Pan, J., Rueckert, D., & Kustner, T. (2021). Motion-Guided Physics-Based Learning for Cardiac MRI Reconstruction. In Michael B. Matthews (Eds.), Conference Record - Asilomar Conference on Signals, Systems and Computers (pp. 900-907). Virtual, Pacific Grove, CA, USA: IEEE Computer Society.

MLA:

Hammernik, Kerstin, et al. "Motion-Guided Physics-Based Learning for Cardiac MRI Reconstruction." Proceedings of the 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021, Virtual, Pacific Grove, CA, USA Ed. Michael B. Matthews, IEEE Computer Society, 2021. 900-907.

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