title: A Joint Acquisition-Estimation Framework for MR Phase Imaging.
abstract: Measuring the phase of the MR signal is faced with fundamental challenges such as phase aliasing, noise and unknown offsets of the coil array. There is a paucity of acquisition, reconstruction and estimation methods that rigorously address these challenges. This reduces the reliability of information processing in phase domain. We propose a joint acquisition-processing framework that addresses the challenges of MR phase imaging using a rigorous theoretical treatment. Our proposed solution acquires the multi-coil complex data without any increase in acquisition time. Our corresponding estimation algorithm is applied optimally voxel-per-voxel. Results show that our framework achieves performance gains up to an order of magnitude compared to existing methods.
authors.forename: Joseph
authors.initials: J
authors.lastname: Dagher
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008959:Models, Neurological; D015233:Models, Statistical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity