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To develop a fast and robust method to resolve phase ambiguity in dual-echo Dixon imaging.A major challenge in dual-echo Dixon imaging is to estimate the phase error resulting from field inhomogeneity. In this work, a binary quadratic optimization program was formulated to resolve the phase ambiguity. A projected power method was developed to efficiently solve the optimization problem. Both the 1-peak fat model and 6-peak fat model were applied to three-dimensional (3D) datasets. Additionally, the proposed method was extended to dynamic magnetic resonance imaging (MRI) applications using the 6-peak fat model. With institutional review board (IRB) approval and patient consent/assent, the proposed method was evaluated and compared with region growing on 29 consecutive 3D high-resolution patient datasets.Fast and robust water/fat separation was achieved by the proposed method in different representative 3D datasets and dynamic 3D datasets. Superior water/fat separation was achieved using the 6-peak fat model compared with the 1-peak fat model. Compared to region growing, the proposed method reduced water/fat swaps from 76 to 7% of the patient cohort.The proposed method can achieve fast and robust phase error estimation in dual-echo Dixon imaging. Magn Reson Med, 2016. © 2016 Wiley Periodicals, Inc.
View details for DOI 10.1002/mrm.26287
View details for PubMedID 27221766
View details for PubMedCentralID PMC5123983