Continuous Globally Optimal Image Segmentation with Local Constraints
نویسندگان
چکیده
The Geodesic Active contour model is a very flexible model for variational image segmentation. Unfortunately the Geodesic Active Contour model exhibits local minima making segmentation results strongly dependent on its initialization. We propose a flexible, interactive segmentation method in two and three dimensions that yields the globally optimal solution with respect to local constraints introduced by the user. A fast numerical scheme is used to minimize the proposed energy which is based on a weighted Total Variation energy functional. With our GPU-based implementation, real-time performance is achieved for both 2D and 3D segmentation problems. We show experimental results on various medical datasets, and discuss the properties of the segmentation framework.
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