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Genetic Algorithms Applied to Image Processing

Ghosh, P., Mitchell, M., and Gold, J. (2010). LSGA: Combining level-sets and genetic algorithms for segmentation. Evolutionary Intelligence, 3, 1-11.

Ghosh, P., Mitchell, M., Tanyi, J. A., and Hung, A. (2009). A genetic algorithm-based level-set curve evolution for prostate segmentation on pelvic CT and MRI images. E. Romero and F. Gonzalez (editors), Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques, ICI Global.

Ghosh, P. and Mitchell, M. (2008). Prostate segmentation on pelvic CT images using a genetic algorithm. in Proceedings of the International Society for Optical Engineering (SPIE), Conference on Medical Imaging, February, 2008. SPIE Press.

Ghosh, P. and Mitchell, M. (2006). Medical image segmentation with genetic algorithms. In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2006, pp. 1171-1178.

Brumby, S. P., Perkins, S. J., Theiler, J., Szymanski, J. J., Bloch, J. J., and Mitchell, M. (1999). Investigation of image feature extraction by a genetic algorithm. In Proceedings of the International Society for Optical Engineering, Proceedings of SPIE 3812, 24-31. Bellingham, WA: SPIE Press.

van Nimwegen, E., Crutchfield, J. P., and Mitchell, M. (1999). Statistical dynamics of the Royal Road genetic algorithm. Theoretical Computer Science, 229 (1), 41–102.

van Nimwegen, E., Crutchfield, J. P., and Mitchell, M. (1997). Finite populations induce metastability in evolutionary search. Physics Letters A, 229 (2), 144-150.

Mitchell, M., Holland, J. H., and Forrest, S. (1994). When will a genetic algorithm outperform hill climbing? In J. D. Cowan, G. Tesauro, and J. Alspector (editors), Advances in Neural Information Processing Systems 6, 51-58, San Mateo, CA: Morgan Kaufmann.

Forrest, S. and Mitchell, M. (1993). What makes a problem hard for a genetic algorithm? Some anomalous results and their explanation. Machine Learning, 13, 285-319.

Forrest, S. and Mitchell, M. (1993). Relative building-block fitness and the building-block hypothesis. In D. Whitley (editor), Foundations of Genetic Algorithms 2, San Mateo, CA: Morgan Kaufmann.

Mitchell, M., Forrest, S., and Holland, J. H. (1992). The royal road for genetic algorithms: Fitness landscapes and GA performance. In F. J. Varela and P. Bourgine (editors), Proceedings of the First European Conference on Artificial Life. Cambridge, MA: MIT Press.





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