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Segmentation of medical images using a genetic algorithm
2006
Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06
Segmentation of medical images is challenging due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Consequently, this task involves incorporating as much prior information as possible (e.g., texture, shape, and spatial location of organs) into a single framework. In this paper, we present a genetic algorithm for automating the segmentation of the prostate on two-dimensional slices of pelvic computed tomography (CT) images. In this approach the
doi:10.1145/1143997.1144183
dblp:conf/gecco/GhoshM06
fatcat:frgl6g3oerbsvjn2r7oxe756sa