Curvature-based representation of objects from range data
Image and Vision Computing
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast level set method for propagating interfaces
Journal of Computational Physics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Volumetric segmentation of medical images by three-dimensional bubbles
Computer Vision and Image Understanding - Special issue on physics-based modeling and reasoning in computer vision
SIAM Review
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation of Carpal Bones from 3d CT Images Using Skeletally Coupled Deformable Models
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Algorithms for implicit deformable models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Vessel Detection by Mean Shift-Based Ray Propagation
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Area and length minimizing flows for shape segmentation
IEEE Transactions on Image Processing
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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A robust and efficient method for the segmentation of 3D structures in CT and MR images is presented. The proposed method is based on 3D ray propagation by mean shift analysis with a smoothness constraint. Specifically, ray propagation is used to guide an evolving surface due to its computational efficiency. In addition, non-parametric analysis and shape priors are incorporated to the proposed technique for robust convergence. Several examples are depicted to illustrate its effectiveness.