Catalytic multiecho phase unwrapping scheme (CAMPUS) in multiecho gradient echo imaging: Removing phase wraps on a voxel‐by‐voxel basis

Abstract

Phase images reflect local field variations including susceptibility contributions and play a key role in a number of imaging applications. However, due to the limited dynamic range of phase values, phase wrapping invariably occurs at long echo times. High pass filtering and region-growing approaches have been common themes in the effort of removing phase wraps. In this article, a novel voxel-by-voxel phase unwrapping scheme taking advantage of short interecho spacing of multiecho gradient echo imaging is proposed. By removing spurious sources of phase variations and exploiting the special features of the flow-induced phase component, phase increments during adjacent echoes can be unveiled that exhibit no phase aliasing. This unaliased phase information is then used to unwrap all the phase images at all of the echoes. Data of 15 volunteers scanned at 3 and 1.5T were processed with the proposed algorithm and two other algorithms in the literature (PhUN and branch cut). It is shown that the proposed approach is fast and effective in unwrapping all the phase values even for voxels in the eyes and the skull, which the other algorithms failed to unwrap. Thus, in multiecho gradient echo imaging, the proposed algorithm has major potential in various applications involving phase processing.