Philippe Boutinaud

The paper introduces a deep learning tool, SHIVA-WMH, for detecting white matter hyperintensities across different WMH severities and demonstrates its superior performance compared to existing methods.

This paper develops a deep learning algorithm for 3D segmentation of perivascular spaces in MRI data, achieving high accuracy and demonstrating interoperability across scanners.

The paper develops a deep learning classifier to assign independent components from resting-state fMRI to predefined resting-state networks, achieving 92% accuracy and creating an RSN atlas.