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A New Particle Swarm Optimization-Based Method for Phase Unwrapping of MRI Data

机译:基于粒子群优化的MRI数据相位展开新方法

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摘要

A new method based on discrete particle swarm optimization (dPSO) algorithm is proposed to solve the branch-cut phase unwrapping problem of MRI data. In this method, the optimal order of matching the positive residues with the negative residues is first identified by the dPSO algorithm, then the branch cuts are placed to join each pair of the opposite polarity residues, and in the last step phases are unwrapped by flood-fill algorithm. The performance of the proposed algorithm was tested on both simulated phase image and MRI wrapped phase data sets. The results demonstrated that, compared with conventionally used branch-cut phase unwrapping algorithms, the dPSO algorithm is rather robust and effective.
机译:提出了一种基于离散粒子群算法(dPSO)的新方法来解决MRI数据的分支切相展开问题。在此方法中,首先通过dPSO算法确定将正残基与负残基匹配的最佳顺序,然后放置分支切口以连接每对相反极性的残基,最后一步,通过洪水将相展开填充算法。在模拟的相位图像和MRI包裹的相位数据集上测试了该算法的性能。结果表明,与常规使用的分支切相展开算法相比,dPSO算法具有较强的鲁棒性和有效性。

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