Author

Mark Peter Maskery

Lancashire Teaching Hospitals NHS Foundation TrustORCID 0000-0001-5661-6267Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Biophysics· 1

Signature Assays, Organisms & Methods

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Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Assay:imaging· 1

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Elizabeth PowelliD· 1 shared Geoff J.M. ParkeriD· 1 shared Hedley C A EmsleyiD· 1 shared Laura M. ParkesiD· 1 shared Paddy J. SlatoriD· 1 shared

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2026-2026 · peak 1/yr

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1 shared paperBiophysics

Elizabeth PowellORCID

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1 paper

Recent·Most cited

BiophysicsNMR in BiomedicinePeer-reviewedMay 11, 2026

Hierarchical Bayesian Modelling Improves Microstructural Parameter Mapping in Diffusion and Exchange MRI Data

Elizabeth Powell, Mark Peter Maskery, Hedley C A Emsley…·Paddy J. Slator

This paper introduces a hierarchical Bayesian modelling approach for diffusion and exchange MRI data, showing improved accuracy and noise resilience compared to traditional least-squares methods.

DOI 10.1002/nbm.70277

imagingBayesian inference

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