Michael Berks

Michael Berks is Research Associate at University of Manchester's Centre for Imaging Sciences. His research develops computational methods for medical image interpretation with applications in oncology and vascular pathology.

Methodological work focuses on machine learning for nailfold capillaroscopy analysis, breast density quantification, and hypoxia imaging. He leads development of open-source tools for quantitative DCE-MRI analysis.

Recent publications demonstrate vascular imaging innovations for systemic sclerosis and oncology applications. Research contributes to Manchester Cancer Research Centre and Digital Futures initiatives.