Level set image segmentation with Bayesian analysis

Neurocomputing

Volumn 71, Issue 10-12, 2008, Pages 1994-2000

  Zhou, Huiyu ^a,b   Yuan, Yuan ^c   Lin, Faquan ^b   Liu, Tangwei ^b  

^a BRUNEL UNIVERSITY   (United Kingdom)

^b GUANGXI MEDICAL UNIVERSITY   (China)

^c ASTON UNIVERSITY   (United Kingdom)

Author keywords

Bayesian analysis; Energy minimisation; Level set; Segmentation

Indexed keywords

ALGORITHMS; BOUNDARY CONDITIONS; IMAGING SYSTEMS; SET THEORY; STATISTICAL METHODS;

BAYESIAN ANALYSIS; ENERGY MINIMIZATION; EXPECTATION-MAXIMIZATION ALGORITHM;

IMAGE SEGMENTATION;

ACCURACY; ALGORITHM; ARTICLE; BAYES THEOREM; CONTROLLED STUDY; ENERGY; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE QUALITY; NOISE; PRIORITY JOURNAL;

EID: 44649174299     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2007.08.035     Document Type: Article

References (14)

1. Caselles R., Kimmel V., and Sapiro G. Geodesic active contour. Int. J. Comput. Vision 22 (1997) 61-79
2. Evans L. Partial Differential Equations (1998), American Mathematical Society, Providence, RI
3. Evans L., and Gariepy R.F. Measure Theory and Fine Properties of Functions (1992), CRC Press, Boca Raton, FL
4. Gomes J., and Faugerus O. Reconciling distance function and level sets. J. Visual Commun. Image Representation 11 (2000) 209-223
5. Kichenassamy S., Kumar A., Olver A., Tannenbaum P., and Yezzi A. Gradient flows and geometric active contour models. Proceedings of the International Conference on Computer Vision (1995)
6. Li C., Xu C., Gui C., and Fox M. Level set evolution without re-initialization: a new variational formulation. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2005)
7. Malladi R., Sethian J., and Vemuri B. Shape modeling with front propagation: a level set approach. IEEE Trans. Pattern Anal. Mach. Intell. 17 (1995) 158-175
8. Mansouri A., Mitiche A., and Vazquez C. Multiregion competition: a level set extension of region competition to multiple region image partitioning. Comput. Vision Image Understanding 101 (2006) 137-150
9. Mumford D., and Shah J. Optimal approximation by piecewise smooth functions and associated variational problems. Commun. Pure Appl. Math. 42 (1989) 577-685
10. Osher S., and Sethian J. Front propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulation. J. Comput. Phys. 79 (1988) 12-49
11. Peng D., Merriman B., Osher S., Zhao H., and Kang M. A PDE-based fast local level set method. J. Comput. Phys. 155 (1999) 410-438
12. Sethian J. Level Set Methods and Fast Marching Methods (1999), Cambridge University Press, Cambridge, MA
13. Vese L., and Chan T. A multiphase level set framework for image segmentation using the Mumford and Shah model. Int. J. Comput. Vision 50 (2002) 271-293
14. Yezzi A., Tsai A., and Willsky A. A fully global approach to image segmentation via coupled curve evolution equations. J. Vision Commun. Image Representation 13 (2002) 195-216