Multidimensional Diffusion MRI Methods With Confined Subdomains

Diffusion Magnetic Resonance Imaging (dMRI) is an imaging technique with exquisite sensitivity to the microstructural properties of heterogeneous media. The conventionally adopted acquisition schemes involving single pulsed field gradients encode random motion water molecules into NMR signal, however typically conflating effects different sources contributing motion. Time-varying magnetic have recently been considered for disentangling such during data encoding phase, opening possibility adding specificity recovered information about medium’s microstructure. Such represented via a diffusion tensor distribution (DTD) model, thus assuming existence several non-exchanging compartments in each which unrestricted. In this work, we consider model that takes confinement account and possesses time-dependence closer restricted diffusion, replace free assumption multidimensional MRI methods. We first demonstrate how captures relevant signal modulations impressed by diffusing both closed spaces, simulated clinically feasible protocol time-varying gradients. Then, provide basis incorporating two dMRI methods, attempt recover (CTD) on human brain dataset.