Purpose: To develop a fast and robust method to resolve phase ambiguity in dual-echo Dixon imaging. Methods: 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. Results: 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. Conclusion: The proposed method can achieve fast and robust phase error estimation in dual-echo Dixon imaging. Magn Reson Med 77:2066–2076, 2017.
All Science Journal Classification (ASJC) codes
- Radiology Nuclear Medicine and imaging
- binary quadratic optimization
- dynamic Dixon
- fat suppression
- two-point Dixon
- water-fat separation