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Unwrapping magnetic resonance phase maps with Chebyshev polynomials.
1Department of Physics and Astronomy, The University of Georgia, Athens, GA 30602, USA.
Magnetic Resonance Imaging
|July 4, 2009
Summary
A novel phase-unwrapping algorithm, using Chebyshev series expansion, accurately processes magnetic resonance (MR) imaging data. This method demonstrates robust performance across synthetic and real-world datasets, including in vivo human and animal scans.
Area of Science:
- Medical Imaging
- Signal Processing
- Computational Science
Background:
- Phase unwrapping is critical for quantitative magnetic resonance (MR) imaging.
- Existing algorithms may struggle with low signal-to-noise ratio (SNR) or magnetic field inhomogeneities.
- Accurate phase unwrapping enhances the diagnostic value of MR scans.
Purpose of the Study:
- To introduce a novel phase-unwrapping algorithm based on the method of moments.
- To evaluate the algorithm's performance on synthetic and experimental MR data.
- To compare the algorithm's results with a widely used existing method.
Main Methods:
- The proposed algorithm utilizes a two-dimensional Chebyshev series expansion for phase map representation.
- Expansion coefficients are determined by exploiting the orthogonality of Chebyshev polynomials.
- Performance is assessed using synthetic data, phantom data, and in vivo human brain and mouse torso MR datasets.
Main Results:
- The algorithm performs well on synthetic data and phantom data, even in low SNR conditions.
- Successful application to in vivo human brain and mouse torso MR data is demonstrated.
- Unwrapped phase maps closely match those generated by the PRELUDE 2D algorithm.
Conclusions:
- The proposed Chebyshev series-based phase-unwrapping algorithm is effective and robust.
- It offers a reliable alternative for quantitative MR imaging, particularly in challenging conditions.
- The algorithm shows comparable performance to established methods like PRELUDE 2D.
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