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Abstract #2411

Water/Fat Decomposition Using Globally Optimal Non-Iterative Graph Surface Estimation

Chen Cui1, Xiaodong Wu1, Milan Sonka1, Mathews Jacob1

1Electrical and Computer Engineering, The University of Iowa, Iowa city, IA, United States

We introduce a novel fat-water decomposition based on non-iterative graph surface estimation.Global optimum of solution is guaranteed through 3D graph searching scheme. Method is applicable to multi-fat peaks situtation. Method are tested on multiple clinical datasets successfully. Computation expense is saved significantly compared to other major algorithms.

Keywords

account accurate addition address adjacent ambiguities analytically applications approaches approximate around assuming attention authors available better challenge challenging chosen city classical clinical complexity computational computer concentrations conducted considerable considerably constrain constrained constraint constraints converge correctly criterion dataset datasets decomposition derived determined discrete either electrical engineering ensure equation estimation even exploit extended fail feasible field foot formulate formulation future global globally good graph great grid growing guarantee guaranteed harmonic illustrating implementation importance improve independently inhomogeneity instead introduce introduced issues iterative knee languages like likelihood linear linearity lipid made make many matrix measure medical medicine merging model models noisy note novel observe often optimal optimization original part peak period pixel pixels plan posed presence problem processing processor programming proposed readily received recently recovery reduce rely resolved restricted retrieval scheme search separation several smooth smoothness solution solutions solve spaced spacing surface swap theoretically took trans uniformly unknowns upper validated variation vector water whose wraps