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Computational diffusion & perfusion MRI in brain imaging

Marco Pizzolato 1 
1 ATHENA - Computational Imaging of the Central Nervous System
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Diffusion and Perfusion Magnetic Resonance Imaging (dMRI & pMRI) represent two modalities that allow sensing important and different but complementary aspects of brain imaging. This thesis presents a theoretical and methodological investigation on the MRI modalities based on diffusion-weighted (DW) and dynamic susceptibility contrast (DSC) images. For both modalities, the contributions of the thesis are related to the development of new methods to improve and better exploit the quality of the obtained signals. With respect to contributions in diffusion MRI, the nature of the complex DW signal is investigated to explore a new potential contrast related to tissue microstructure. In addition, the complex signal is exploited to correct a bias induced by acquisition noise of DW images, thus improving the estimation of structural scalar metrics. With respect to contributions in perfusion MRI, the DSC signal processing is revisited in order to account for the bias due to bolus dispersion. This phenomenon prevents the correct estimation of perfusion metrics but, at the same time, can give important insights about the pathological condition of the brain tissue. The contributions of the thesis are presented within a theoretical and methodological framework, validated on both synthetical and real images.
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Submitted on : Tuesday, October 24, 2017 - 3:06:15 PM
Last modification on : Saturday, June 25, 2022 - 11:27:52 PM


Version validated by the jury (STAR)


  • HAL Id : tel-01536335, version 2



Marco Pizzolato. Computational diffusion & perfusion MRI in brain imaging. Other. Université Côte d'Azur, 2017. English. ⟨NNT : 2017AZUR4017⟩. ⟨tel-01536335v2⟩



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