Neural networks parametrize level sets for Chan-Vese segmentation via equivalence to polygonal approximations, with unsupervised training providing data-driven geometric priors that improve initialization and convergence.
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Neural network parametrized level sets for image segmentation
Neural networks parametrize level sets for Chan-Vese segmentation via equivalence to polygonal approximations, with unsupervised training providing data-driven geometric priors that improve initialization and convergence.