Title | Phase unwrapping with graph cuts optimization and dual decomposition acceleration for 3D high-resolution MRI data. |
Publication Type | Journal Article |
Year of Publication | 2017 |
Authors | Dong J, Chen F, Zhou D, Liu T, Yu Z, Wang Y |
Journal | Magn Reson Med |
Volume | 77 |
Issue | 3 |
Pagination | 1353-1358 |
Date Published | 2017 03 |
ISSN | 1522-2594 |
Keywords | Algorithms, Cerebral Hemorrhage, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Magnetic Resonance Imaging, Reproducibility of Results, Sensitivity and Specificity, Signal Processing, Computer-Assisted |
Abstract | 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 three-dimensional 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 the computational efficiency of 3D graph cut-based phase unwrapping algorithms. Magn Reson Med 77:1353-1358, 2017. © 2016 International Society for Magnetic Resonance in Medicine. |
DOI | 10.1002/mrm.26174 |
Alternate Journal | Magn Reson Med |
PubMed ID | 26997158 |
Grant List | R43 EB015293 / EB / NIBIB NIH HHS / United States R01 EB013443 / EB / NIBIB NIH HHS / United States R01 CA178007 / CA / NCI NIH HHS / United States |
Related Institute:
MRI Research Institute (MRIRI)