Max A. Viergever

This study investigates how inaccuracies in response function calibration affect fiber orientation distribution (FOD) characteristics and fiber tracking in diffusion MRI.

This paper introduces a scanner harmonization method for diffusion MRI data using adaptive dictionary learning, preserving biological variability while reducing scanner-induced variability.

This paper introduces automated methods to estimate noise distributions in diffusion MRI data using Gamma distribution moments and maximum likelihood, showing improved accuracy over Rician assumptions.

This study shows that using ordinary linear least squares (OLLS) in diffusion tensor imaging (DTI) group analyses can inflate effect sizes and increase false positives compared to iterative weighted linear least squares (IWLLS).

This paper introduces diffusion profile realignment to reduce variability in along-tract dMRI analysis by improving alignment across subjects, enhancing detection of regional changes.

The paper identifies a new white matter tract, the superoanterior fasciculus, using diffusion MRI tractography and validates it across multiple cohorts and techniques.