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Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
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Online image reconstruction via Multiple Orthogonal Reference Sensitivity Encoding (MORSE).

Oliver Josephs1, Barbara Dymerska2, Nadine N Graedel1

  • 1The Functional Imaging Laboratory, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK.

Magma (New York, N.Y.)
|July 4, 2026
PubMed
Summary
This summary is machine-generated.

A new MRI method, Multiple Orthogonal Reference Sensitivity Encoding (MORSE), efficiently estimates coil sensitivities and reconstructs images. This computationally fast technique enables online deployment for high-quality, artifact-free MRI scans.

Keywords:
Image reconstructionParallel imagingRegularised SENSESensitivity estimation

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Imaging
  • Computational Imaging

Background:

  • Parallel imaging accelerates MRI acquisition but relies on accurate coil sensitivity estimation.
  • Current sensitivity estimation methods can be computationally intensive, hindering real-time applications.
  • Robust coil sensitivity estimation is crucial for high-quality image reconstruction in undersampled MRI.

Purpose of the Study:

  • To develop a computationally efficient method for estimating coil sensitivities and reconstructing undersampled MRI images.
  • To enable online deployment of MRI reconstruction techniques through reduced computation time.
  • To present a data-driven regularized SENSE formalism suitable for Cartesian k-space acquisitions.

Main Methods:

  • Introduced Multiple Orthogonal Reference Sensitivity Encoding (MORSE) for estimating multiple sensitivities per voxel.
  • MORSE addresses challenges like varying sensitivities, chemical shift artifacts, and limited fields of view.
  • Integrated a data-driven regularization term for noise control and adaptability.

Main Results:

  • MORSE demonstrated successful deployment in neuroimaging studies at 3T and 7T, including functional and quantitative MRI.
  • Applied MORSE to liver and knee imaging, showcasing its versatility beyond brain applications.
  • Consistently achieved high-quality, artifact-free images with reconstruction times suitable for online use, outperforming other methods.

Conclusions:

  • MORSE offers a flexible and robust approach to sensitivity estimation and image unfolding.
  • The method is provided as an open-source library within the Gadgetron framework for community access.
  • This advancement facilitates faster and more adaptable MRI reconstruction for diverse clinical applications.