Inferring and comparing structural parcellations of the human brain using diffusion MRI

Abstract : Understanding how brain connectivity is organized, and how this constrains brain functionality is a key question of neuroscience. The advent of Diffusion Magnetic Resonance Imaging (dMRI) permitted the in vivo estimation of brain axonal connectivity. In this thesis, we leverage these advances in order to: study how the brain connectivity is organized; study the relationship between brain connectivity, anatomy, and function; find correspondences between structurally-defined regions of different subjects, and infer connectivity in the presence of a brain’s pathology. We present three major contributions. Our first contribution is a model for the long-range axonal connectivity, and an efficient technique to divide the brain in regions with homogeneous connectivity. Our parceling technique can create both single-subject and groupwise structural parcellations of the brain. The resulting parcels are in agreement with anatomical, structural and functional parcellations extant in the literature. Our second contribution is a method to find correspondence between structural parcellations of different subjects. Based on Optimal Transport, it performs significantly better than the state-of-the-art ones. Our third contribution is a multi-atlas technique to infer the location of white-matter bundles in patients with a brain pathology. As existent techniques, our approach aggregates spatial information from healthy subjects, our novelty is to weight such information with the diffusion image of the patient. We show that our technique achieves better results than the non-weighted methods.
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Guillermo Alejandro Gallardo Diez. Inferring and comparing structural parcellations of the human brain using diffusion MRI. Signal and Image processing. Université Côte d'Azur, 2018. English. ⟨NNT : 2018AZUR4233⟩. ⟨tel-02272039⟩

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