Abstract #2611

Pseudo-Random Center Placement O-Space Imaging: Optimizing Incoherence for Compressed Sensing

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.