Deformable models are segmentation techniques that adapt a curve with the goal of
maximizing its overlap with the actual contour of an object of interest within an image. Such …

This paper describes a hybrid level set approach for medical image segmentation. This new
geometric deformable model combines region-and edge-based information with the prior …

We explore the application of genetic algorithms (GA) to deformable models through the
proposition of a novel method for medical image segmentation that combines GA with …

In this paper, the localization of structures in biomedical images is considered as a
multimodal global continuous optimization problem and solved by means of soft computing …

This paper studies the optimization problem of topological active net (TAN), which is often
seen in image segmentation and shape modeling. A TAN is a topological structure …

Image segmentation is the critical task of partitioning an image into multiple objects.
Deformable Models are effective tools aimed at performing image segmentation. Among …

The Topological Active Model is an active model focused on segmentation tasks. It provides
information about the surfaces and the inside of the detected objects in the scene. The …

We performed a combination of differential evolution and a multiobjective approach for the
optimization of topological active nets, a deformable model that integrates features of region …

Energy minimization is of particular interest in medical image analysis. In the past two
decades, a variety of optimization schemes have been developed. In this paper, we present …

This paper presents a two-phase method to segment the hippocampus in histological
images. The first phase represents a training stage where, from a training set of manually …