Carlo M. Pierpaoli

The paper develops a method to detect and correct EPI artifacts in diffusion MRI using 4-way phase-encoding data, improving reproducibility and reducing ghost artifacts.

The paper introduces Pscore, a percentile-based metric to assess individual deviations in non-Gaussian diffusion MRI metrics, showing improved accuracy over Zscore in skewed distributions.

This paper introduces an empirical method to correct gradient nonlinearity in multi-site diffusion weighted MRI, improving reproducibility across scanners and sessions.

This paper introduces a 2D diffusion MRI framework to specifically assess axonal injury and spinal cord microenvironments, showing strong correlation with histological findings.

The paper describes neuroimaging processing methods for the ABCD Study to extract brain phenotypes from multimodal imaging data.

This study evaluates modern diffusion tractography methods using a standardized challenge, finding no significant improvement in anatomical accuracy despite methodological advances.