Phase data for quantitative susceptibility mapping must be unwrapped to remove ambiguities due to limitations in the collected data. This work demonstrates the advantages of quality-guided region-growing over conventionally used methods and introduces a general method to correct for temporal discontinuities introduced by path-based spatial unwrapping methods. The unwrapping approaches were evaluated in 11 in vivo datasets presenting a variety of phase profiles.
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