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Phase unwrapping with a rapid opensource minimum spanning tree algorithm (ROMEO).
- Source :
-
Magnetic resonance in medicine [Magn Reson Med] 2021 Apr; Vol. 85 (4), pp. 2294-2308. Date of Electronic Publication: 2020 Oct 26. - Publication Year :
- 2021
-
Abstract
- Purpose: To develop a rapid and accurate MRI phase-unwrapping technique for challenging phase topographies encountered at high magnetic fields, around metal implants, or postoperative cavities, which is sufficiently fast to be applied to large-group studies including Quantitative Susceptibility Mapping and functional MRI (with phase-based distortion correction).<br />Methods: The proposed path-following phase-unwrapping algorithm, ROMEO, estimates the coherence of the signal both in space-using MRI magnitude and phase information-and over time, assuming approximately linear temporal phase evolution. This information is combined to form a quality map that guides the unwrapping along a 3D path through the object using a computationally efficient minimum spanning tree algorithm. ROMEO was tested against the two most commonly used exact phase-unwrapping methods, PRELUDE and BEST PATH, in simulated topographies and at several field strengths: in 3T and 7T in vivo human head images and 9.4T ex vivo rat head images.<br />Results: ROMEO was more reliable than PRELUDE and BEST PATH, yielding unwrapping results with excellent temporal stability for multi-echo or multi-time-point data. It does not require image masking and delivers results within seconds, even in large, highly wrapped multi-echo data sets (eg, 9 seconds for a 7T head data set with 31 echoes and a 208 × 208 × 96 matrix size).<br />Conclusion: Overall, ROMEO was both faster and more accurate than PRELUDE and BEST PATH, delivering exact results within seconds, which is well below typical image acquisition times, enabling potential on-console application.<br /> (© 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)
- Subjects :
- Animals
Head
Magnetic Resonance Imaging
Rats
Algorithms
Brain diagnostic imaging
Subjects
Details
- Language :
- English
- ISSN :
- 1522-2594
- Volume :
- 85
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Magnetic resonance in medicine
- Publication Type :
- Academic Journal
- Accession number :
- 33104278
- Full Text :
- https://doi.org/10.1002/mrm.28563