Robust phase unwrapping for MR temperature imaging using a magnitude-sorted list, multi-clustering algorithm

• Published in: Magnetic resonance in medicine Vol. 73; no. 4; pp. 1662 - 1668
• Main Authors: Maier, Florian, Fuentes, David, Weinberg, Jeffrey S., Hazle, John D., Stafford, R. Jason
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01-04-2015; Wiley Subscription Services, Inc
• Subjects: Algorithms; Body Temperature - physiology; Brain - anatomy & histology; Brain - physiology; Humans; Image Interpretation, Computer-Assisted - methods; Magnetic Resonance Imaging - methods; MRI; multi-clustering; phase unwrapping; Reproducibility of Results; Sensitivity and Specificity; sorted list; Thermography - methods; thermometry; multi-clustering; sorted list; MRI; thermometry; phase unwrapping
• ISSN: 0740-3194; 1522-2594
• DOI: 10.1002/mrm.25279

Purpose
Several methods in MRI use the phase information of the complex signal and require phase unwrapping (e.g., B0 field mapping, chemical shift imaging, and velocity measurements). In this work, an algorithm was developed focusing on the needs and requirements of MR temperature imaging applications.
Methods
The proposed method performs fully automatic unwrapping using a list of all pixels sorted by magnitude in descending order and creates and merges clusters of unwrapped pixels until the entire image is unwrapped. The algorithm was evaluated using simulated phantom data and in vivo clinical temperature imaging data.
Results
The evaluation of the phantom data demonstrated no errors in regions with signal‐to‐noise ratios of at least 4.5. For the in vivo data, the algorithm did not fail at an average of more than one pixel for signal‐to‐noise ratios greater than 6.3. Processing times less than 30 ms per image were achieved by unwrapping pixels inside a region of interest (53 × 53 pixels) used for referenceless MR temperature imaging.
Conclusions
The algorithm has been demonstrated to operate robustly with clinical in vivo data in this study. The processing time for common regions of interest in referenceless MR temperature imaging allows for online updates of temperature maps without noticeable delay. Magn Reson Med 73:1662–1668, 2015. © 2014 Wiley Periodicals, Inc.