Mohammad Golbabaee1 and Clarice Poon1
1University of Bath, Bath, United Kingdom
1University of Bath, Bath, United Kingdom
We introduce a novel off-the-grid sparse approximation algorithm for multicompartment MRF. The proposed algorithm is an accurate and importantly a scalable alternative to the multicompartment MRF baselines because it does not rely on fine-gridded multiparametric MRF dictionaries.
Mixture maps (margins cropped) of the WM, GM and a CSF related compartments for the in-vivo brain using different MC-MRF algorithms.
Estimated T1/T2 values (milliseconds) for in-vivo WM, GM compartments using MC-MRF algorithms compared to the 1.5T literature values in [11]* and [12]+.