Global Minimum for Active Contour Models: A Minimal Path Approach
International Journal of Computer Vision
A Level-Set Approach to 3D Reconstruction from Range Data
International Journal of Computer Vision
Efficient estimation of 3D Euclidean distance fields from 2D range images
VVS '02 Proceedings of the 2002 IEEE symposium on Volume visualization and graphics
A Level-Set Approach for the Metamorphosis of Solid Models
IEEE Transactions on Visualization and Computer Graphics
Elastically Adaptive Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation of 3D Medical Structures Using Robust Ray Propagation
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
A Windows-Based User Friendly System for Image Analysis with Partial Differential Equations
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
Journal of Computational Physics
A Geometric Approach to Segmentation and Analysis of 3D Medical Images
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
Segmentation of biological volume datasets using a level-set framework
VG'01 Proceedings of the 2001 Eurographics conference on Volume Graphics
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This paper presents a framework for implicit deformable models and a pair of new algorithms for solving the nonlinear partial differential equations that result from this framework. Implicit models offer a useful alternative to parametric models, particularly when dealing with the deformation of higher-dimensional objects. The basic expressions for the evolution of implicit models are relatively straightforward; they follow as a direct consequence of the chain rule for differentiation. More challenging, however, is the development of algorithms that are stable and efficient. The first algorithm is a viscosity approximation which gives solutions over a dense set in the range, providing a means of calculating the solutions of embedded families of contours simultaneously. The second algorithm incorporates sparse solutions for a discrete set of contours. This sparse-field method requires a fraction of the computation compared to the first but offers solutions only for a finite number of contours. Results from 3d medical data as well as video images are shown.