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Modélisation géométrique, simplification et visualisation des fibres de la matière blanche du cerveau

Abstract : Tractography data (fibers) obtained from diffusion MRI present several challenges.In this thesis, we propose some useful methods and algorithms for simplification, visualization, and manipulation of these data.We introduce a new multi-resolution representation for tractograms, faster, and with higher geometric accuracy than existing simplification approaches.We also investigate various geometric representations and focus on moving least square (MLS) projection with algebraic point set surfaces (APSS), on which we reduce the complexity, allowing for the use of global kernels for analysis and modeling.A segmentation technique using the multi-resolution representation is presented, achieving better reproducibility than other approaches.Tractograms being massive, we also introduce a compression algorithm taking advantage of data obtention from diffusion MRI.The algorithm speed even allows for the direct use of compressed data for visualization, as it can be decompressed on-the-fly on the GPU.This research and the obtained results lie at the intersection between Computer Graphics and Medical Data Analysis, paving the way for numerous perspectives.
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Submitted on : Friday, April 2, 2021 - 5:37:05 PM
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  • HAL Id : tel-03189123, version 1

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Corentin Mercier. Modélisation géométrique, simplification et visualisation des fibres de la matière blanche du cerveau. Medical Imaging. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAT048⟩. ⟨tel-03189123⟩

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