Seed prioritized unwrapping (SPUN) for MR phase imaging

Background Region‐growing‐based phase unwrapping methods have the potential for lossless phase aliasing removal, but generally suffer from unwrapping error propagation associated with discontinuous phase and/or long calculation times. The tradeoff point between robustness and efficiency of phase unw...

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Veröffentlicht in:Journal of magnetic resonance imaging 2019-07, Vol.50 (1), p.62-70
Hauptverfasser: Ye, Yongquan, Zhou, Fei, Zong, Jinguang, Lyu, Jingyuan, Chen, Yanling, Zhang, Shuheng, Zhang, Weiguo, He, Qiang, Li, Xueping, Li, Ming, Zhang, Qinglei, Qing, Zhao, Zhang, Bing
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Sprache:eng
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Zusammenfassung:Background Region‐growing‐based phase unwrapping methods have the potential for lossless phase aliasing removal, but generally suffer from unwrapping error propagation associated with discontinuous phase and/or long calculation times. The tradeoff point between robustness and efficiency of phase unwrapping methods in the region‐growing category requires improvement. Purpose To demonstrate an accurate, robust, and efficient region‐growing phase unwrapping method for MR phase imaging applications. Study Type Prospective. Subjects, Phantom normal human subjects (10) / brain surgery patients (2) / water phantoms / computer simulation. Field Strength/Sequence 3 T/gradient echo sequences (2D and 3D). Assessment A seed prioritized unwrapping (SPUN) method was developed based on single‐region growing, prioritizing only a portion (eg, 100 seeds or 1% seeds) of available seed voxels based on continuity quality during each region‐growing iteration. Computer simulation, phantom, and in vivo brain and pelvis scans were performed. The error rates, seed percentages, and calculation times were recorded and reported. SPUN unwrapped phase images were visually evaluated and compared with Laplacian unwrapped results. Statistical Tests Monte Carlo simulation was performed on a 3D dipole phase model with a signal‐to‐noise ratio (SNR) of 1–9 dB, to obtain the mean and standard deviation of calculation error rates and calculation times. Results Simulation revealed a very robust unwrapping performance of SPUN, reaching an error rate of
ISSN:1053-1807
1522-2586
DOI:10.1002/jmri.26606