This article surveys deformable models, a promising and vigorously researched computerassisted medical image analysis technique. Among model-based techniques, deformable models offer a unique and powerful approach to image analysis that combines geometry, physics, and approximation theory. They have proven to be effective in segmenting, matching, and tracking anatomic structures by exploiting (...

We have developed a new approach to shape-based tracking and analysis of cardiac MR images using geometrically deformable templates (GDTs). We propose to use an energyminimizing deformable template which can deform into similar shapes under the in uence of external forces. The degree of deformation of the template from its equilibrium shape is expressed by the amount of bending energy which is ...

Active contour and surface models, also known as deformable models, constitute a class of powerful segmentation techniques. Geometric deformable models implemented via level-set methods have advantages over parametric ones due to their intrinsic behavior, parameterization independence, and ease of implementation. However, a long claimed advantage of geometric deformable models — the ability to ...

In this paper, we present a real-time simulation and visualization framework that models a deformable surface lung model with tumor, simulates the tumor motion and predicts the amount of radiation doses that would be deposited in the moving lung tumor during the actual delivery of radiation. The model takes as input a subject-specific 4D Computed Tomography (4D CT) of lungs and computes a defor...

This paper presents a deformable model based approach for automated segmentation of kidneys from tree dimensional (3D) abdominal CT images. Since the quality of an input image is very poor and noisy due to the large slice thickness, we use a deformable model represented by NURBS surface, which uses not only the gray level appearance of the target but also statistical information of the shape. A...

This paper presents a method to perform 2D deformable object tracking using the boundary element method (BEM). BEM, like the finite element method (FEM), is a technique to model an elastic solid. BEM differs from FEM in that only the contour of an object needs to be meshed for BEM, making this method attractive for computer vision problems. For FEM, the interior of the object must be meshed als...

We present a method for simulating the active contraction of deformable models, usable for interactive animation of soft deformable objects. We present a novel physical principle as the governing equation for the coupling between the low dimensional 1D activation force model and the higher dimensional 2D/3D deformable model. Our activation splines are easy to set up and can be used for physics ...

We introduce a new approach to medical image analysis that combines deformable model methodologies with concepts from the field of artificial life. In particular, we propose "deformable organisms", autonomous agents whose task is the automatic segmentation, labeling, and quantitative analysis of anatomical structures in medical images. Analogous to natural organisms capable of voluntary movemen...

In this paper we present an interactive method for simulating deformable objects using skeletal constraints. We introduce a two-way coupling of a finite element model and a skeleton that is attached to this model. The skeleton pose is determined via inverse kinematics. The target positions of joints are either given by user interactions or forces imposed by the surrounding deformable body. The ...

A local deformable-model-based segmentation can be very helpful to extract objects from an image, especially when no prototype about the object is available. However, this technique can drive to an erroneous segmentation in noisy images, in case of the active contour is captured by noise particles. If some geometrical information (a priori knowledge) of the object is available, then it can be u...