Alexander Leemans

This study uses diffusion MRI to examine limbic system white matter development in children and adolescents with ADHD, finding reduced microstructural organization and connectivity linked to symptom severity.

This paper introduces RISH-GLM, a method to harmonize diffusion MRI data across sites without requiring matched training subjects, showing effectiveness with unmatched groups and multiple sites.

The paper correlates sensory processing sensitivity proxy scores with diffusion tensor imaging measures in a large sample, identifying axonal microstructural differences associated with SPS traits.

This paper introduces a novel fiber tractography method that improves the reconstruction of the corticospinal tract by incorporating anatomical priors and multi-level fiber orientation analysis.

The paper evaluates tractography methods using a macaque dataset to determine optimal approaches for mapping brain pathways from multi-shell diffusion MRI.

This study evaluates variability in white matter bundle segmentation across 42 groups using the same dataset, finding protocol variability exceeds other sources of inconsistency.

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 a method to estimate multiple fiber orientation distributions in both white and grey matter using tissue-specific response functions and multi-shell diffusion MRI, improving cortical fiber tractography.

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 evaluates tractography reproducibility using empirical data from a single healthy volunteer scanned on two scanners, finding high consistency among top algorithms but variability due to tract volume containment.

This paper evaluates the fractal dimension as a marker of structural brain complexity in MRI, showing improved accuracy with scale optimization and highlighting registration's impact on FD estimates.

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

The paper evaluates tractography methods by analyzing a simulated dataset, finding that most algorithms generate many false-positive connections.