Boundary vector field for parametric active contours

Pattern Recognition

Volumn 40, Issue 6, 2007, Pages 1635-1645

  Sum, K W ^a   Cheung, Paul Y S ^a  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Boundary vector field; Capture range; Concave object extraction; External forces; Gradient vector flow; Image segmentation; Medical image analysis; Parametric active contours; Snakes

Indexed keywords

BOUNDARY CONDITIONS; COMPUTER VISION; IMAGE PROCESSING; INTERPOLATION; PROBLEM SOLVING; REQUIREMENTS ENGINEERING; VECTORS;

BOUNDARY VECTOR FIELDS; CONCAVE OBJECT EXTRACTION; GRADIENT VECTOR FLOW; MEDICAL IMAGE ANALYSIS;

FEATURE EXTRACTION;

EID: 33947186695     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2006.11.006     Document Type: Article

References (31)

1. M. Kass, A. Witkin, D. Terzopoulos, Snakes: active contour modes, Int. J. Comput. Vision (1988) 321-331.
2. Xu C., and Prince J.L. Snakes, shapes, and gradient vector flow. IEEE Trans. Image Process. 7 3 (1998) 359-369
3. Cohen L.D., and Cohen I. Finite-element methods for active contour models and balloons for 2-D and 3-D images. IEEE Trans. Pattern Anal. Mach. Intell. 15 11 (1993)
4. Amini A.A., Weymouth T.E., and Jain R.C. Using dynamic programming for solving variational problems in vision. IEEE Trans. Pattern Anal. Mach. Intell. 12 9 (1990) 855-867
5. Velasco F.A., and Marroquin J.L. Growing snakes: active contours for complex topologies. Pattern Recognition 36 (2003) 475-482
6. Yezzi J.A., Kichenassamy S., Kumar A., Olver P., and Tannenbaum A. A geometric snake model for segmentation of medical imagery. IEEE Trans. Med. Imaging 16 2 (1997) 199-209
7. Caselles V., Catte F., Coll T., and Dibos F. A geometric model for active contours in image processing. Numer. Math. 66 (1993) 1-31
8. Caselles V., Kimmel R., and Sapiro G. Geodesic active contours. Int. J. Comput. Vision 22 (1997) 61-79
9. Chan T.F., and Vese L.A. Active contours without edges. IEEE Trans. Image Process. 10 2 (2001) 266-277
10. Malladi R., Sethian J.A., and Vemuri B.C. Shape modeling with front propagation: a level set approach. IEEE Trans. Pattern Anal. Mach. Intell. 17 2 (1995) 158-179
11. Siddiqi K., Lauziere Y.B., Tannenbaum A., and Zucker S.W. Area and length minimizing flows for shape segmentation. IEEE Trans. Image Process. 7 3 (1998) 433-443
12. Vasilerskiy A., and Siddiqi K. Flow maximizing geometric flows. IEEE Trans. Pattern Anal. Mach. Intell. 24 12 (2002) 1565-1578
13. P. Brigger, J. Hong, M. Unser, B-spline snakes: a flexible tool for parametric contour detection, IEEE Trans. Image Process. (2000) 1484-1496.
14. Leymarie F., and Levine M.D. Tracking deformable objects in the plane using an active contour models. IEEE Trans. Pattern Anal. Mach. Intell. 15 6 (1993) 617-634
15. Pardas M., and Sayrol E. Motion estimation based tracking of active contours. Pattern Recognition Lett. 22 (2001) 1447-1456
16. Rosmussen C., and Hager G.D. Probabilistic data association methods for tracking complexes visual objects. IEEE Trans. Pattern Anal. Mach. Intell. 23 6 (2001) 560-576
17. Cohen L.D. On active contour models and balloon. CVGIP: Image Understanding 53 2 (1991) 211-218
18. Davatzikos C., and Prince J.L. An active contour model for mapping the cortex. IEEE Trans. Med. Imaging 4 3 (1995) 65-80
19. Tang J., and Acton S.T. Vessel boundary tracking for intravital microscopy via multiscale gradient vector flow snakes. IEEE Trans. Biomed. Eng. 51 2 (2004)
20. Xie X., and Mirmehdi M. RAGS: region-aided geometric snake. IEEE Trans. Image Process. 13 5 (2004)
21. Paragios N., Mellina-Gottardo O., and Ramesh V. Gradient vector flow fast geometric active contours. IEEE Trans. Pattern Anal. Mach. Intell. 26 3 (2004)
22. Ray N., Acton S.T., and Ley K. Tracking leukocytes in vivo with shape and size constrained active contours. IEEE Trans. Medical Imaging 21 10 (2002)
23. Ray N., and Acton S.T. Motion gradient vector flow: an external force for tracking rolling leukocytes with shape and size constrained active contours. IEEE Trans. Med. Imaging 23 12 (2004)
24. Erkol B., Moss R.H., Stanley R.J., Stoecker W.V., and Hvatum E. Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes. Skin Res. Technol. 11 (2005) 17-26
25. Dumitras A., and Venetsanopoulos A.N. Angular map-driven snakes with application to object shape description in color images. IEEE Trans. Image Process. 10 12 (2001)
26. Chuang C.H., and Lie W.N. A downstream algorithm based on extended gradient vector flow field for object segmentation. IEEE Trans. Image Process. 13 10 (2004)
27. Canero C., Vilarino F., Mauri J., and Radeva P. Predictive (un)distortion model and 3-D reconstruction by biplane snakes. IEEE Trans. Med. Imaging 21 9 (2002)
28. Prasad V.S.N., and Yegnanarayana B. Finding axes of symmetry from potential fields. IEEE Trans. Image Process. 13 12 (2004)
29. Wei M., Zhou Y., and Wan M. A fast snake model based on non-linear diffusion for medical image segmentation. Computerized Med. Imaging Graphics 28 (2004) 109-117
30. K.W. Sum, P.Y.S. Cheung, A fast parametric snake model with enhanced concave object extraction capability, Proc. of IEEE ISSPIT, 2006.
31. Horn B.K.P., and Schunck B.G. Determining optical flow. Artif. Intell. 17 (1981) 185-203