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Resolving phase ambiguity in dual-echo dixon imaging using a projected power method.

Tao Zhang1,2, Yuxin Chen3, Shanshan Bao1

  • 1Department of Radiology, Stanford University, Stanford, California, USA.

Magnetic Resonance in Medicine
|May 26, 2016
PubMed
Summary

This study presents a fast and robust method for phase ambiguity resolution in dual-echo Dixon imaging, significantly improving water/fat separation accuracy. The new technique reduces water/fat swaps in patients compared to existing methods.

Keywords:
binary quadratic optimizationdynamic Dixonfat suppressiontwo-point Dixonwater-fat separation

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Area of Science:

  • Medical Imaging
  • Magnetic Resonance Imaging (MRI)
  • Image Processing

Background:

  • Dual-echo Dixon imaging is crucial for water/fat separation in MRI.
  • Phase ambiguity due to field inhomogeneity presents a significant challenge.
  • Accurate phase error estimation is vital for reliable water/fat separation.

Purpose of the Study:

  • To develop a fast and robust method for resolving phase ambiguity in dual-echo Dixon imaging.
  • To improve the accuracy and reliability of water/fat separation.
  • To address the challenge of phase error estimation in inhomogeneous magnetic fields.

Main Methods:

  • Formulated a binary quadratic optimization program to resolve phase ambiguity.
  • Developed a projected power method for efficient optimization.
  • Applied 1-peak and 6-peak fat models to 3D datasets and extended to dynamic MRI.
  • Evaluated the method on 29 patient datasets and compared with region growing.

Main Results:

  • Achieved fast and robust water/fat separation in 3D and dynamic datasets.
  • Demonstrated superior performance with the 6-peak fat model compared to the 1-peak model.
  • Reduced water/fat swaps from 76% to 7% in the patient cohort compared to region growing.

Conclusions:

  • The proposed method provides fast and robust phase error estimation in dual-echo Dixon imaging.
  • This advancement enhances the clinical utility of Dixon imaging techniques.
  • The optimized approach leads to more accurate water/fat separation in MRI scans.