A new particle swarm optimization-based method for phase unwrapping of MRI data.
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.
Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Wei
W
He
Yiyuan
Y
Cheng
Ling
L
Xia
Feng
F
Liu
D000465:Algorithms; D003198:Computer Simulation; D003952:Diagnostic Imaging / Q000379:methods; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D015203:Reproducibility of Results