Evidence map›Paper›PMID 42400765›Full record

ArticleMagma (New York, N.Y.)2026

Online image reconstruction via Multiple Orthogonal Reference Sensitivity Encoding (MORSE).

Oliver Josephs, Barbara Dymerska, Nadine N Graedel, Yael Balbastre, Nadège Corbin, Martina F Callaghan

Abstract read
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In one paragraph

Article in Magma (New York, N.Y.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Oliver Josephs *The Functional Imaging Laboratory, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK.
Barbara Dymerska *The Functional Imaging Laboratory, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK. b.dymerska@ucl.ac.uk.ORCID http://orcid.org/0000-0001-6339-2169
Nadine N GraedelThe Functional Imaging Laboratory, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK.
Yael BalbastreExperimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK.
Nadège CorbinCentre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/University Bordeaux, Bordeaux, France.
Martina F CallaghanThe Functional Imaging Laboratory, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK.

Funding

Wellcome Trust 203147/Z/16/ZWellcome Trust 226793/Z/22/Z
6 · The paper itself

Abstract

objectiveParallel imaging is ubiquitous in MRI, enabling higher spatial and/or temporal resolution. However, successful unfolding is contingent on robust and accurate estimation of relative coil sensitivities, which often involves computation times that preclude online deployment. We present a computationally efficient method of robustly estimating coil sensitivities, and reconstructing under-sampled images using a data-driven regularised SENSE formalism that is commensurate with online deployment for Cartesian k-space acquisitions. MATERIALS AND

methodsThe proposed image reconstruction method via Multiple Orthogonal Reference Sensitivity Encoding (MORSE) estimates multiple sensitivities per voxel to address issues, such as rapidly varying sensitivities, chemical shift artefact, or insufficient fields of view. It simultaneously provides a data-driven regularisation term for noise control providing inherent adaptability to diverse imaging contexts.

resultsMORSE has been successfully deployed in multiple neuroimaging studies at both 3T and 7T, including functional studies of autobiographical memory processing, visual and auditory perception, and quantitative MRI studies of neurodegenerative diseases including Huntington's, Alzheimer's and Parkinson's. Exemplar image reconstructions are presented and compared with GRAPPA, ENLIVE, ESPIRiT and LORAKS. We also showcase application of MORSE outside of the brain via application in liver and knee imaging. MORSE consistently produced high-quality, artefact-free images with reconstruction times feasible for online deployment. DISCUSSION: The proposed method of sensitivity estimation and unfolding regularisation is flexible and robust. It is made available to the community in open-source as a library of functions within the vendor-agnostic Gadgetron image reconstruction framework.

Indexed as

Image reconstructionParallel imagingRegularised SENSESensitivity estimation

Identifiers

PMID42400765

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.