Leo K. Tam1, Gigi Galiana2, Jason P. Stockmann3, Andrew Dewdney4, Terence W. Nixon2, Dana C. Peters2, Robert Todd Constable2, 5
1Biomedical Engineering, Yale University, New Haven, CT, United States; 2Diagnostic Radiology, Yale University, New Haven, CT, United States; 3Martinos Center, Massachusetts General Hospital, Boston, MA, United States; 4Siemens AG Healthcare, Erlangen, Bavaria, Germany; 5Neurosurgery, Yale University, New Haven, CT, United States
O-space imaging has shown distributed artifacts due to non-linear encoding via spatially-varying center placements (CPs). The success of non-linear encoding methods in the image domain lead to development of an approach to maximize incoherence in a sparse transform domain such as the Daubeuchies wavelets. By pseudo-randomizing CPs, an incoherence optimized O-space acquisition produced superior reconstructions under a compressed sensing framework.