Segmentation of medical images using a genetic algorithm

GECCO 2006 - Genetic and Evolutionary Computation Conference

Volumn 2, Issue , 2006, Pages 1171-1178

  Ghosh, Payel ^a   Mitchell, Melanie ^b  

^a PORTLAND STATE UNIVERSITY   (United States)

^b Department of Electrical and Computer Engineering   (United States)

Author keywords

Genetic Algorithms; Level Set Methods; Texture Segmentation

Indexed keywords

COMPUTERIZED TOMOGRAPHY; FEATURE EXTRACTION; GENETIC ALGORITHMS; MEDICAL IMAGING; SET THEORY; TISSUE;

ANATOMICAL LANDMARKS; LEVEL SET METHODS; TEXTURE SEGMENTATION;

IMAGE SEGMENTATION;

EID: 33750236759     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1143997.1144183     Document Type: Conference Paper

References (22)

1. Cagnoni, A., Dobrzeniecki, A. B., Poli, R., and Yanch, J. C. Genetic algorithm-based interactive segmentation of 3D medical images. Image and Vision Computing, 17(12), 881-895, 1999.
2. Caselles, V., Kimmel, R., and Shapiro, G. Geodesic active contours. Int. J. Comput. Vis., 22, 61-79, 1998.
3. Chan, T., and Vese, L. Active contours without edges. IEEE Trans. Image Proc., 10, 266-277, 2001.
4. Cohen, L. On active contour models and balloons. CVGIP: Image Understanding, 53, 211-218, 1991.
5. Daida, J.M., Hommes, J. D., Bersano-Begey, T.F., Ross, S. J, and Vesecky, J. F. Algorithm discovery using the genetic programming paradigm: Extracting low-contrast curvilinear features from SAR images of Arctic ice. In Advances in Genetic Programming 2, P. J. Angeline, and K. E. Kinnear, Jr., editors, chap. 21, MIT, Cambridge, 1996.
6. Harris, C., and Buxton, B. Evolving edge detectors with genetic programming. In Koza, J. R., Goldberg, D. E., Fogel, D. B., and Riolo, R. L., editors, Genetic Programming 1996: Proceedings of the First Annual Conference, pp. 309-315. MIT Press, 1996.
7. Harvey, N., Levenson, R. M., Rimm, D. L. Investigation of automated feature extraction techniques for applications in cancer detection from multi-spectral histopathology images. Proc. of SPIE 2003, 5032, 557-566.
8. Harvey, N., Perkins, S., Brumby, S. P., Theiler, J., Porter, R. B., Young, A. C., Verghese, A. K., Szymanski J. J., and Bloch, J. J. Finding golf courses: The ultra high-tech approach. Lecture Notes in Computer Science, vol. 1803, pp.54-64, 2000.
9. Kass, M., Witkin, A., and Terzopoulos, D. Snakes: Active contour models. Intl. J. Computer Vision, 1, 321-331, 1988.
10. Laws, K. I. Rapid texture identification. SPIE, Image Processing for Missile Guidance, 238, 376-380, 1980.
11. Laws, K. I. Texture Image Segmentation. PhD dissertation, Univ. of Southern Calif., Jan. 1980.
12. Leventon, M., Grimson, E., and Faugeras, O. Statistical shape influence in geodesic active contours. In Proc. IEEE Conf. on Computer Vision andPatt. Recog., 1, 316-323, 2000.
13. Malladi, R., Sethian, J. A., and Vemuri, B. C. Shape modeling with front propagation: A level set approach. IEEE Trans. on Patt. Recog. and Machine Intell., 17(2), 158-175, 1995.
14. Mitchell, M., An Introduction to Genetic Algorithms, Cambridge, MA, MIT Press, (1996).
15. Nordin, P., and Banzhaf, W. Programmatic compression of images and sound. In Genetic Programming 1996, Proceedings of the First Annual Conference, Koza J. R. et al. editors, pp. 345-350, MIT Press, 1996.
16. Perkins, S., Theiler, J., Brumby, S. P., Harvey, N. R., Porter, R. B., Szymanski, J. J., and Bloch J. J. GENIE: A Hybrid Genetic Algorithm for Feature Classification in Multi-Spectral Images. Proc. SPIE 4120 Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation III, pp. 52-62, 2000.
17. Pham, D. L., Xu, C., Prince, J. L. Survey of current methods in medical image segmentation. Annual Review of Biomedical Eng., 2, pp. 315-337, 2000.
18. Poli, R., and Cagoni, S. Genetic programming with user-driven selection: Experiments on the evolution of algorithms for image enhancement. In Genetic Programming 1997, Proceedings of the 2nd Annual Conference, J. R. Koza et al. editors, pp. 269-277, 1997.
19. Sonka, M., Hlavac, V., and Boyle, R. Image Processing, Analysis and Machine Vision. London, Chapman & Hall, UK, 1994.
20. Tsai, A., Yezzi, A., Wells, W., Tempany, C., Tucker, D., Fan, A., Grimson, E., Willsky A. A shape-based approach to the segmentation of medical imagery using level sets. IEEE Trans. on Medical Imaging, 22, 137-154, 2003.
21. Tsai, A., Wells, W., Warfield, S., Willsky; A. An EM algorithm for shape classification based on level sets. Medical Image Analysis, Vol. 9, No. 5, 491-502, October 2005.
22. Vese L. A., Chan, T. F. A multiphase level set framework for image segmentation using the Mumford and Shah model. Intl. J. Computer Vision, 50(3), 271-293, 2002.