Artemis Zavaliangos‐Petropulu

HARMONY harmonizes neuroimaging data from multiple cohorts to study brain-behavior associations in anxious misery disorders, showing increased statistical power in pooled analyses.

This study finds that smaller ipsilesional hippocampal volume is associated with worse upper limb sensorimotor impairment in chronic stroke patients, with a stronger effect in women.

This study shows that global brain health, measured by brain age, influences post-stroke sensorimotor outcomes and mediates the effect of lesion damage.

This study finds that smaller spared subcortical nuclei are linked to worse sensorimotor outcomes after stroke, varying by time since stroke and type of impairment.

This study compares a new convolutional neural network-based hippocampal segmentation method (Hippodeep) with existing methods on stroke MRIs, finding Hippodeep more accurate in quality control and spatial accuracy.

This study identifies subcortical shape differences in MDD patients using ENIGMA data, highlighting region-specific changes in surface area and thickness.

The paper analyzes diffusion MRI data from ADNI3 to assess how different protocols affect diffusion indices and their association with cognitive impairment and age.

The paper develops deep learning models to assess the quality of subcortical brain shape models from MRI, reducing human rater time by 46-70%.

The paper evaluates 15 candidate SNPs associated with psychiatric disorders using 6,165 diffusion MRI scans, finding no significant associations after correction for multiple testing.

This work uses machine learning to automate quality control of 3D brain shape models, reducing human workload by 30-70% across multiple datasets and diseases.