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MORSE: Multiple Orthogonal Reference Sensitivity Encoding

Oliver Josephs,B. Dymerska,Nadine N. Graedel,Yaël Balbastre,Nadège Corbin,Martina F. Callaghan

Published 2025 in Unknown venue

ABSTRACT

Parallel imaging is ubiquitous in MRI, enabling diverse applications such as ultra-high-resolution functional and quantitative imaging with greater temporal resolution or reduced scan times respectively. Successful unfolding is contingent on robust and accurate estimation of the relative coil sensitivities, which often involves computation times that preclude real-time deployment. Here we present a computationally-efficient method of robustly estimating coil sensitivities, and reconstructing under-sampled images using a data-driven regularised SENSE formalism. Our MORSE scheme estimates multiple sensitivities per voxel to address issues such as rapidly varying sensitivities, chemical shift artefact, or insufficient fields of view and provides a data-driven regularisation term for noise control. Exemplar structural and functional image reconstructions at 3T and 7T are presented and compared with a vendor-provided GRAPPA reconstruction as well as state-of-the-art ESPIRiT and LORAKS algorithms. MORSE consistently produced high-quality, artefact-free images with reconstruction times feasible for real-time deployment. It is flexible and robust, and made available to the community in open-source as a library of functions within the vendor-agnostic Gadgetron image reconstruction framework.

PUBLICATION RECORD

  • Publication year

    2025

  • Venue

    Unknown venue

  • Publication date

    2025-10-10

  • Fields of study

    Medicine, Physics, Engineering

  • Identifiers
    arXiv 2510.09098
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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