activity
20202026
most citedConFiG: Contextual Fibre Growth to generate realistic axonal packing for diffusion MRI simulation

44 citations · 46 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Medical Image Alignment Assessment as a Test of Generalist Visual Reasoning in Frontier Multimodal Models

Ross Callaghan, Niannu Gao, Hojjat Azadbakht +1

Frontier multimodal large language models (MLLMs) are increasingly positioned as general purpose visual reasoners as part of the quest for artificial general intelligence. A key te…

cs.CV2026

Eddeep: a deep-learning framework for fast eddy-current distortion correction in diffusion MRI

Antoine Legouhy, Ross Callaghan, Yuchuan Qiao +4

Diffusion MRI (dMRI) relies on diffusion-weighted echo-planar imaging, which is highly susceptible to eddy-current-induced geometric distortions. These distortions vary across diff…

cs.CV2026

When Brains Disagree: Biological Ambiguity Underlies the Challenge of Amyloid PET Synthesis from Structural MRI

Louise E. G. Baron, Ross Callaghan, David M. Cash +3

Structural MRI-to-amyloid PET synthesis has been proposed as a non-invasive alternative for amyloid assessment in Alzheimer's disease (AD). However, reported performance of identic…

cs.CV2026

Polaffini: A feature-based approach for robust affine and polyaffine image registration

Antoine Legouhy, Cosimo Campo, Ross Callaghan +2

In this work we present Polaffini, a robust and versatile framework for anatomically grounded registration. Medical image registration is dominated by intensity-based registration…

cs.CV2025

NimbleReg: A light-weight deep-learning framework for diffeomorphic image registration

Antoine Legouhy, Ross Callaghan, Nolah Mazet +3

This paper presents NimbleReg, a light-weight deep-learning (DL) framework for diffeomorphic image registration leveraging surface representation of multiple segmented anatomical r…

cs.CV2024

POLAFFINI: Efficient feature-based polyaffine initialization for improved non-linear image registration

Antoine Legouhy, Ross Callaghan, Hojjat Azadbakht +1

This paper presents an efficient feature-based approach to initialize non-linear image registration. Today, nonlinear image registration is dominated by methods relying on intensit…

eess.IV2024★ 2 cited

Eddeep: Fast eddy-current distortion correction for diffusion MRI with deep learning

Antoine Legouhy, Ross Callaghan, Whitney Stee +3

Modern diffusion MRI sequences commonly acquire a large number of volumes with diffusion sensitization gradients of differing strengths or directions. Such sequences rely on echo-p…

physics.med-ph2021

Impact of within-voxel heterogeneity in fibre geometry on spherical deconvolution

Ross Callaghan, Daniel C. Alexander, Marco Palombo +1

Axons in white matter have been shown to have varying geometries within a bundle using ex vivo imaging techniques, but what does this mean for diffusion MRI (dMRI) based spherical…

physics.med-ph2020★ 44 cited

ConFiG: Contextual Fibre Growth to generate realistic axonal packing for diffusion MRI simulation

Ross Callaghan, Daniel C. Alexander, Marco Palombo +1

This paper presents Contextual Fibre Growth (ConFiG), an approach to generate white matter numerical phantoms by mimicking natural fibre genesis. ConFiG grows fibres one-by-one, fo…