title: Sparse-representation-based direct minimum L (p) -norm algorithm for MRI phase unwrapping.
abstract: A sparse-representation-based direct minimum L (p) -norm algorithm is proposed for a two-dimensional MRI phase unwrapping. First, the algorithm converts the weighted-L (p) -norm-minimization-based phase unwrapping problem into a linear system problem whose system (coefficient) matrix is a large, symmetric one. Then, the coefficient-matrix is represented in the sparse structure. Finally, standard direct solvers are employed to solve this linear system. Several wrapped phase datasets, including simulated and MR data, were used to evaluate this algorithm's performance. The results demonstrated that the proposed algorithm for unwrapping MRI phase data is reliable and robust.
authors.affiliation: Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
authors.forename: Wei
authors.initials: W
authors.lastname: He
authors.affiliation: Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
authors.forename: Ling
authors.identifier: 0000-0002-1937-9693
authors.initials: L
authors.lastname: Xia
authors.affiliation: School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD 4072, Australia.
authors.forename: Feng
authors.initials: F
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006257:Head / Q000502:physiology; D006321:Heart / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007717:Knee / Q000502:physiology; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D015203:Reproducibility of Results