A new segmentation method using deformable models was defined for medical image segmentation. As deformable model we used Topological Active Nets, model which integrates features of region-based and boundary-based segmentation techniques. The model deformation is controlled by an Artificial Neural Network (ANN) that learns how to move the nodes of the model based on their energy surrounding. The ANN is applied to each of the nodes and in different temporal steps until the final segmentation is reached. The ANN training is obtained by simulated evolution, using Differential Evolution to automatically obtain the ANN that provides the emergent segmentation. The methodology was adapted and tested in two different medical domains, that is, CT medical images and eye fundus images to demonstrate the potential of the segmentation technique.
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