AUTHORS: de Skowronski A, Palombo M, Novikov DS, Jelescu I

ISMRM & SMRT Annual Meeting, : , Online, May 2021


ABSTRACT

Developing a relevant model for brain gray matter is a complex task. As opposed to white matter, features such as inter-compartment water exchange or soma should likely be modeled. In this work we examine the performance of a variant of the Karger Model, called GRAMM I, that accounts for exchange, both on synthetic and experimental data. We show q-t coverage is necessary for reliable model parameter estimation at the individual voxel level and compare two regression approaches. Future work includes protocol optimization and the extension of the GRAMM I model to account for soma.

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