Author

Paul McCarthy

University of Oxford

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Neuroscience· 6

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Assay:imaging· 6 Organism:human· 4 Approach:statistical model· 4 Research Focus:benchmarking· 3 Research Focus:batch correction / integration· 2 Approach:experimental assay· 2 Research Focus:database / resource· 1 Approach:deep learning· 1

Frequent Co-Authors

Stephen M. SmithiD· 5 shared Fidel Alfaro-AlmagroiD· 4 shared Gwenaëlle DouaudiD· 3 shared Jesper AnderssoniD· 3 shared Karla L. MilleriD· 3 shared Ludovica GriffantiiD· 3 shared Thomas E. NicholsiD· 3 shared Mark JenkinsoniD· 2 shared

Activity by Year

2017-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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5 shared papersNeuroscience

Stephen M. SmithORCID

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6 papers

Recent·Most cited

Diagnose Harmonisation (DHARM): An open-source tool for the harmonisation and analysis of batch effects in MRI-derived measures.

Jacob Turnbull, Gaurav Bhalerao, Thomas E. Nichols, Paul McCarthy, Grace Gillis, Jasmine Blane, Brian Zhaoyi Mo, Shaun Warrington, Stamatios N. Sotiropoulos, Renato Besenczi, Fidel Alfaro-Almagro, Stephen M. Smith, Ludovica Griffanti

DHARM is an open-source tool that diagnoses, harmonizes, and evaluates batch effects in MRI data using standardized workflows and multivariate diagnostics.

bioRxiv · Nov 3, 2026 · PreprintNeuroscience

MMORF - FSL's MultiMOdal Registration Framework

Frederik Lange, Christoph Arthofer, Andreas Bartsch, Gwenaëlle Douaud, Paul McCarthy, Stephen M. Smith, Jesper Andersson

MMORF is a nonlinear image registration tool for MRI brain images that outperforms existing methods in accuracy and distortion control across multiple domains.

Imaging Neuroscience · Jan 1, 2024Peer-reviewedNeuroscience

Integrating large-scale neuroimaging research datasets: harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets

Valentina Bordin, Ilaria Bertani, Irene Mattioli, Vaanathi Sundaresan, Paul McCarthy, Sana Suri, Enikő Zsoldos, Nicola Filippini, Abda Mahmood, Luca Melazzini, Maria Marcella Laganà, Giovanna Zamboni, Archana Singh‐Manoux, Mika Kivimaki B, Klaus P. Ebmeier, , Ludovica Griffanti

This paper harmonises white matter hyperintensity measurements across two neuroimaging datasets by standardising preprocessing and modelling demographic and physiological differences.

NeuroImage · May 19, 2021Peer-reviewedNeuroscience

Confound modelling in UK Biobank brain imaging

Fidel Alfaro‐Almagro, Paul McCarthy, Soroosh Afyouni, Jesper Andersson, Matteo Bastiani, Karla L. Miller, Thomas E. Nichols, Stephen M. Smith

This paper identifies and analyzes potential confounds in UK Biobank brain imaging data, emphasizing their impact on statistical analyses and suggesting considerations for future studies.

NeuroImage · Jun 2, 2020Peer-reviewedNeuroscience

Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations

Stephen M. Smith, Lloyd T. Elliott, Fidel Alfaro‐Almagro, Paul McCarthy, Thomas E. Nichols, Gwenaëlle Douaud, Karla L. Miller

The paper identifies 62 distinct modes of brain aging from multimodal imaging data, showing varied genetic and lifestyle associations.

eLife · Mar 5, 2020Peer-reviewedNeuroscience

Image Processing and Quality Control for the first 10,000 Brain Imaging Datasets from UK Biobank

Fidel Alfaro‐Almagro, Mark Jenkinson, Neal K. Bangerter, Jesper Andersson, Ludovica Griffanti, Gwenaëlle Douaud, Stamatios N. Sotiropoulos, Saâd Jbabdi, Moisés Hernández-Fernández, Emmanuel Vallée, Diego Vidaurre, Matthew Webster, Paul McCarthy, Chris Rorden, Alessandro Daducci, , Stephen M. Smith

The paper describes an automated processing and quality control pipeline for brain imaging data from the first 10,000 UK Biobank participants.

NeuroImage · Oct 24, 2017Peer-reviewedNeuroscience