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Alexander Leemans

Researcher at Utrecht University

Publications -  306
Citations -  21500

Alexander Leemans is an academic researcher from Utrecht University. The author has contributed to research in topics: Diffusion MRI & Fractional anisotropy. The author has an hindex of 64, co-authored 289 publications receiving 17932 citations. Previous affiliations of Alexander Leemans include Australian Catholic University & Cardiff University.

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Microstructural maturation of the human brain from childhood to adulthood.

TL;DR: Differences observed in developmental timing suggest a pattern of maturation in which areas with fronto-temporal connections develop more slowly than other regions, which is consistent with previous postmortem and imaging studies.
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The B-matrix must be rotated when correcting for subject motion in DTI data.

TL;DR: A systematic study to investigate the effect of neglecting to reorient the B‐matrix on DTI data during motion correction is presented and the consequences for diffusion fiber tractography are discussed.
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The challenge of mapping the human connectome based on diffusion tractography

Klaus H. Maier-Hein, +76 more
TL;DR: The encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent) is reported, however, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups.

ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data

TL;DR: The ExploreDTI toolbox as mentioned in this paper is a non-commercial package that combines many of the key diffusion processing tools that have appeared in the recent literature, but which have not necessarily been widely available.
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Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging.

TL;DR: More robust estimates of the proportion of affected voxels, the number of fiber orientations within each WM voxel, and the impact on tensor‐derived analyses are provided, using large, high‐quality diffusion‐weighted data sets, with reconstruction parameters optimized specifically for this task.