Current surgical simulations that involve cutting with scissors lack display of forces "between the fingers" of the operator. The objective of this work is to develop a fast, realistic haptic rendering technique for scissor cutting that can be easily integrated into soft tissue models commonly used in surgical simulators. A virtual environment was created for combined graphic and haptic display...

This paper develops a general approach for the efficient modeling and animation of non-rigid multibody objects. We develop a new family of physics-based modeling primitives that can undergo free motions as well as parameterized and free-form deformations. Starting with parameterized geometric primitives and adding global geometric deformations, local finite-element deformations, mass distributi...

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

This paper reviews model based methods for non rigid shape analysis and recognition These methods model match and classify non rigid shapes which are generally problematic for conventional algorithms using rigid models Issues including deformable model represen tation optimization criteria formulation model matching and classi cation are examined in detail The emphasis of this paper is on D def...

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 ...

Deformable models integrate bottom-up information derived from image appearance cues and top-down priori knowledge of the shape. They have been widely used with success in medical image analysis. One limitation of traditional deformable models is that the information extracted from the image data may contain gross errors, which adversely affect the deformation accuracy. To alleviate this issue,...

This thesis deals with surface extraction from noisy volumetric images, which is a common problem in medical image analysis. Due to noise, the use of a-priori information about surface topology and shape is necessary for automatic surface extraction methods. Deformable surface models can incorporate such geometric knowledge into extraction process which is restated as an energy minimization pro...