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Abstract #3275

A Novel Phase Unwrapping Method Based on Pixel Clustering and Local Surface Fitting with Application to Water-Fat Separation

Junying Cheng1,2, Yingjie Mei2,3, Biaoshui Liu2, Xiaoyun Liu1, Ed. X. Wu4,5, Wufan Chen1,2, and Yanqiu Feng2,4,5

1School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China, People's Republic of, 2School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China, People's Republic of, 3Philips Healthcare, Guangzhou, China, People's Republic of, 4Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, China, People's Republic of, 5Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, China, People's Republic of

Current phase-unwrapping algorithms are challenged by rapid phase variations, noise and disconnected regions. We propose a novel phase-unwrapping method based on the observation the phase local difference (pLD) and complex local difference (cLD) maps. The proposed algorithm first clusters pixels into disconnected regions by thresholding the cLD map and then performs local polynominal surface fitting (LPSF) to unwrap phase with the knowledge of wrapping locations identified by thresholding the pLD map. Both simulation and in vivo results demonstrate that the proposed method can correctly unwrapped phase even in the presence of rapid phase variation, low SNR, and disconnected regions, and has great potential application to phase-related MRI in practice.

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