Christian Kames1,2, Jonathan Doucette1,2, and Alexander Rauscher1,2,3
1UBC MRI Research Centre, The University of British Columbia, Vancouver, BC, Canada, 2Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC, Canada, 3Department of Pediatrics, The University of British Columbia, Vancouver, BC, Canada
1UBC MRI Research Centre, The University of British Columbia, Vancouver, BC, Canada, 2Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC, Canada, 3Department of Pediatrics, The University of British Columbia, Vancouver, BC, Canada
A
second order method decreases reconstruction times by more than 10x
compared to a first order method for solving nonlinear dipole
inversion in quantitative susceptibility mapping.
Table 1. Convergence study. We computed the number of iterations of each iterative scheme which resulted in the lowest NRMSE when compared to COSMOS, multi-orientation NDI, and multi-orientation HANDI for five different datasets.
Table 3. Comparison of NRMSE for HANDINet, variational network NDI (VaNDI), and variational network with standard dipole deconvolution (VarNet).