Abstract：In order to develop an effective method to solve the phase unwrapping problem in the susceptibility weighted imaging (SWI), this paper analyzed and compared eight kinds of spatial domain unwrapping algorithms, among which five global optimization algorithms were selected, including WLS (weighted least square), PRELUDE (phase region expanding labeler for unwrapping discrete estimations), PUMA (phase unwrapping max-flow/min-cut), ARM (accumulation of residual maps), and SL-MC (sorted list, multi-clustering); and three integral algorithms were selected, including Branch-cut, WFF-QG (windowed Fourier-filtered and quality-guided method), and PUROR (phase unwrapping using recursive orthogonal referring). Experiments were carried out by using two sets of MATLAB simulation images and two sets of 1.5T real SWI data provided by Alltech. The reliability of the unwrapping methods was evaluated by using differences between wrapped and re-wrapped phase and time. The results show that the P±|M| value of PUROR was zero and it had the fastest running time, which implied the application potential in clinical practices.
李心灵, 唐铭, 刘奇. 相位解缠绕算法在磁敏感加权图像中的应用与比较[J]. 中国生物医学工程学报, 2018, 37(2): 129-137.
Li Xinling, Tang Ming, Liu Qi. The Application and Comparison of Phase Unwrapping Algorithms in Susceptibility Weighted Images. Chinese Journal of Biomedical Engineering, 2018, 37(2): 129-137.
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