We present a novel evolutionary computing based approach to medical image segmentation. Our method complements the image-pixel integration power of deformable shape models with the high-level control mechanisms of genetic algorithms (GA). Specifically, the GAs alleviate typical deformable model weaknesses pertaining to model initialization, deformation parameter selection, and energy functional...

Estimating probabilistic deformable template models is a new approach in the fields of computer vision and probabilistic atlases in computational anatomy. A first coherent statistical framework modelling the variability as a hidden random variable has been given by Allassonnière, Amit and Trouvé in [1] in simple and mixture of deformable template models. A consistent stochastic algorithm has be...

teraction, global-to-local deformations, shape statistics, setting low-level parameters, and incorporating new forces or energy terms. However, incorporating expert knowledge to automatically guide deformations can not be easily and elegantly achieved using the classical deformable model low-level energy-based fitting mechanisms. In this chapter we review Deformable Organisms, a decision-making...

Open-loop adaptive optics is a technique in which the turbulent wavefront is measured before it hits the deformable mirror for correction. We present a technique to model a deformable mirror working in open-loop based on multivariate adaptive regression splines (MARS), a non-parametric regression technique. The model's input is the wavefront correction to apply to the mirror and its output is t...

Recovery of unstructured 3D data with deformable models has been the subject of many studies over the last ten years. In particular, in medical image understanding, deformable models are useful to get a precise representation of anatomical structures. However, general deformable models involve large linear systems to solve when dealing with high resolution 3D images. The advantage of parametric...

We present a new approach to shape-based segmentation and tracking of multiple, deformable anatomical structures in cardiac MR images. We propose to use an energy-minimizing geometrically deformable template (GDT) which can deform into similar shapes under the in uence of image forces. The degree of deformation of the template from its equilibrium shape is measured by a penalty function associa...

Segmentation of medical images is an important step in various applications such as visualization, quantitative analysis and image-guided surgery. Numerous segmentation methods have been developed in the past two decades for extraction of organ contours on medical images. Low-level segmentation methods, such as pixel-based clustering, region growing, and filter-based edge detection, require add...

In this paper we propose a technique for 3-D segmentation of abdominal aorta computed tomography (CT) images. Output data of the proposed algorithm is a 3-D model of aorta that can be used for measurement of aortas dimensions. Thos information are very important in minimally invasive treatment of abdominal aortic aneurysm. The technique is based on deformable model. The deformable model is impl...

A finite-element deformable surface-spine model is developed in this paper to register two surfaces by recovering the nonlinear deformation with respect to each other. The deformable surface-spine model is a dynamic model governed by Lagrangian motion equations. A 9 degree-of-freedom (dof) finite-element surface element and a $-dof spine element are developed to iteratively solve Lagrangian equ...

In this paper, we present a method for simulating the interaction of fluids with deformable solids. The method is designed for the use in interactive systems such as virtual surgery simulators where the real-time interplay of liquids and surrounding tissue is important. In computer graphics, a variety of techniques have been proposed to model liquids and deformable objects at interactive rates....