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Abstract #4041

Multi-compartment T2 relaxometry Model using Gamma Distribution representations: A framework for Quantitative Estimation of Brain Tissue Microstructures.

Sudhanya Chatterjee1, Olivier Commowick2, Simon K. Warfield3, and Christian Barillot4

1VisAGeS, IRISA U746, Universite de Rennes-1, Rennes, France, 2VisAGeS Inserm U746, IRISA, Inria, Rennes, France, 3Boston Children’s Hospital, Boston, MA, United States, 4VisAGeS, INRIA/IRISA, Inserm U746, CNRS, Rennes, France

Advanced MRI techniques (e.g. – d-MRI, MT, relaxometry etc.) can provide quantitative information of brain tissues. Image voxels are often heterogeneous in terms of microstructure information due to physical limitations and imaging resolution. Quantitative assessment of the brain tissue microstructure can provide valuable insights into neurodegenerative diseases (e.g. - Multiple Sclerosis). In this work, we propose a multi-compartment model for T2-Relaxometry to obtain brain microstructure information in a quantitative framework. The proposed method allows simultaneous estimation of the model parameters.

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