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A semi-automated modelling pipeline to predict the mechanics of multiple sclerosis lesion afflicted brains from magnetic resonance images | Synapse
March 3, 2026
Open Access
A semi-automated modelling pipeline to predict the mechanics of multiple sclerosis lesion afflicted brains from magnetic resonance images
AS
Adam C. Szekely-Kohn
University of Birmingham
DO
Diana Cruz De Oliveira
MC
Marco Castellani
The Edgbaston Hospital
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Puntos clave
The approach predicts brain mechanics with an accuracy rate of around 80%.
Using a semi-automated modelling pipeline, researchers analyze magnetic resonance images to assess lesion effects.
The analysis incorporates advanced imaging techniques to enhance predictive capabilities of brain lesions.
This technique may enable more personalized treatment strategies for individuals with multiple sclerosis.
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Szekely-Kohn et al. (Wed,) studied this question.
synapsesocial.com/papers/69a760e1c6e9836116a2e0c8
https://doi.org/https://doi.org/10.1016/j.compbiomed.2026.111519