Published May 7, 2022 | Version v1
Conference paper Open

The deep SECRET to accelerated first-pass perfusion cardiac MRI

Authors/Creators

  • 1. Laboratorio de Procesado de Imagen, Universidad de Valladolid, Valladolid, Spain
  • 2. School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
  • 3. Institute for Systems and Robotics, Lisbon, Portugal; Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
  • 4. Centre for Marine Sciences - CCMAR, Faro, Portugal; School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom

Description

First-pass perfusion cardiac magnetic resonance (FPP-CMR) is becoming essential to detect blow flow anomalies. However, the need for real-time acquisitions limits the achievable spatial resolution and coverage of the heart. To keep both within a reasonable range, FPP-CMR needs to be accelerated. A SElf-Supervised aCcelerated REconsTruction (SECRET) DL framework is presented to speed-up reconstruction of FPP-CMR images from undersampled (k,t)-space data. The physical reconstruction models are used to train deep neural networks without requiring fully sampled images. SECRET achieves good quality reconstructions at a variety of acceleration rates, with significant speed-ups compared to the state-of-the-art.

Notes

This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 867450. (OPTIMAR: OPTical Imaging of Molecular and signalling Activity in Real-time: application to flatfish metamorphosis, https://cordis.europa.eu/project/id/867450).

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Additional details

Funding

European Commission
OPTIMAR - OPTical Imaging of Molecular and signalling Activity in Real-time: application to flatfish metamorphosis 867450