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.