A topology preserving deformable model using level sets

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 2, Issue , 2001, Pages

  Han, Xiao ^a   Xu, Chenyang ^a   Prince, Jerry L ^a  

^a JOHNS HOPKINS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; EDGE DETECTION; LAGRANGE MULTIPLIERS; TOPOLOGY;

DIGITAL IMAGES;

IMAGE SEGMENTATION;

EID: 0035696551     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. Snakes: Active contour models
2. On active contour models and balloons
3. Snakes, shapes, and gradient vector flow
4. A geometric model for active contours in image processing
5. Shape modeling with front propagation: A level set approach
6. Geodesic active contours
7. A geometric snake models for segmentation of medical imagery
8. Area and length minimizing flow for shape segmentation
9. Deformable models in medical image analysis: A survey
10. Reconstruction of the human cerebral cortex from magnetic resonance images
11. Automated 3-D extraction of inner and outer surfaces of cerebral cortex from MRI
12. Topologically constrained cortical surfaces from MRI
13. Automated manifold surgery: Constructing geometrically accurate and topologically correct models of the human cerebral cortex
14. Detection of 3D simple points for topology preserving transformations with application to thinning
15. Simple points, topological numbers and geodesic neighborhoods in cubic grids
16. From 3D magnetic resonance images to structural representations of the cortex topography using topology preserving deformations
17. Image segmentation through operators based on topology
18. Marching cubes: A high-resolution 3D surface construction algorithm
19. On generating topologically consistent iso-surfaces from uniform samples