Phase unwrapping with graph cuts optimization and dual decomposition acceleration for 3D high-resolution MRI data.

Purpose: Existence of low SNR regions and rapid-phase variations pose challenges to spatial phase unwrapping algorithms. Global optimization-based phase unwrapping methods are widely used, but are significantly slower than greedy methods. In this paper, dual decomposition acceleration is introduced to speed up a threedimensional graph cut-based phase unwrapping algorithm. Methods: The phase unwrapping problem is formulated as a global discrete energy minimization problem, whereas the technique of dual decomposition is used to increase the computational efficiency by splitting the full problem into overlapping subproblems and enforcing the congruence of overlapping variables. Using three dimensional (3D) multiecho gradient echo images from an agarose phantom and five brain hemorrhage patients, we compared this proposed method with an unaccelerated graph cut-based method. Results: Experimental results show up to 18-fold acceleration in computation time. Conclusions: Dual decomposition significantly improves thecomputational efficiency of 3D graph cut-based phase unwrapping algorithms. (C) 2016 International Society forMagnetic Resonance inMedicine