activity
20242026
most citedUncertainty quantification for White Matter Hyperintensity segmentation detects silent failures and improves automated Fazekas quantification

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2026

Multi-task learning for the automatic grading of enlarged perivascular space burden using MRI

Jesse Phitidis, William N. Whiteley, Joanna M. Wardlaw +11

Enlarged perivascular spaces (PVS) visible in brain magnetic resonance imaging (MRI) are increasingly thought to be linked to poor brain health. PVS are elongated structures of les…

q-bio.NC2026

Subcortical Shape Variations and Their Associations with Cognition Across the 8th Decade of Life. A Study in the Lothian Birth Cohort 1936

Maria del C. Valdes-Hernandez, Wonjung Park, Joanna Moodie +7

The study of brain morphology changes in normal individuals may capture aspects of functionally-relevant brain aging not fully indicated by gross volumetry. Despite the important r…

q-bio.NC2025

Multiplex Nodal Modularity: A novel network metric for the regional analysis of amnestic mild cognitive impairment during a working memory binding task

Avalon Campbell-Cousins, Federica Guazzo, Mark Bastin +2

Modularity is a well-established concept for assessing community structures in various single and multi-layer networks, including those in biological and social domains. Brain netw…

eess.IV2024★ 1 cited

Uncertainty quantification for White Matter Hyperintensity segmentation detects silent failures and improves automated Fazekas quantification

Ben Philps, Maria del C. Valdes Hernandez, Chen Qin +8

White Matter Hyperintensities (WMH) are key neuroradiological markers of small vessel disease present in brain MRI. Assessment of WMH is important in research and clinics. However,…