Medical image segmentation by level set method incorporating region and boundary statistical information

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3287, Issue , 2004, Pages 654-660

  Lin, Pan ^a   Zheng, Chongxun ^a   Yang, Yong ^a   Gu, Jianwen ^a  

^a XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTERIZED TOMOGRAPHY; DROP BREAKUP; EVOLUTIONARY ALGORITHMS; HYDROGELS; IMAGE SEGMENTATION; LEVEL MEASUREMENT; MEDICAL IMAGE PROCESSING; MEDICAL IMAGING; PATTERN RECOGNITION; STATISTICS;

BOUNDARY INFORMATION; CLASSICAL METHODS; CONVENTIONAL METHODS; IMAGE BOUNDARIES; LEVEL SET FRAMEWORK; LEVEL SET METHOD; NUMERICAL TECHNIQUES; STATISTICAL INFORMATION;

NUMERICAL METHODS;

EID: 35048867867     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30463-0_82     Document Type: Article

References (9)

1. S. J. Osher and J. A. Sethian. Fronts propagating with curvature dependent speed: Algorithms based on Hamilton-Jacobi formulations. J. Comput. Phys, vol. 79, pp. 12-49,1988.
2. R. Malladi, J. Sethian, and B. Vemuri. Shape modeling with front propagation: A level set approach. IEEE T-PAM1, vol. 17, no. 2, pp. 158-175,1995.
3. A. Chakraborty, L. Staib, and J. Duncan. Deformable boundary finding in medical image by integrating gradient and region information. IEEE T-MI, vol. 15, no. 6, pp. 859-870,1996.
4. R. Ronfard. Region-based strategies for active contour models. International Journal of Computer Vision, vol. 13, no. 2, pp. 229-251,1994.
5. C.S .Poon and M. Braun. Image segmentation by a deformable contour model incorporating region analysis. Phys. Med. Biol, vol. 42, no. 9, pp. 1833-1841,1997.
6. C. Xu, A. Yezzi. Jr, and J. Prince. On the relationship between parametric and geometric active contours. Technical Report JHU/ECE 99-14, Dec. 1999.
7. C. Baillard and C. Barillot. Robust 3D segmentation of anatomical structures with level sets. Proceedings of MICCAl 2000. pp. 237-245, 2000.
8. H.Voorhees and T.Poggio. Detecting textons and texture boundaries in natural images. Proc.of the International Conference on Computer Vision, pp.250-258, 1987.
9. S. Geman and D. Geman. Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.6, pp.721-741,1984.