Non linear image processing proves to be a powerful tool for segmenting images preserving only the interesting regions; those are the cells's nucleous (CN) in this application. All CN are preserved and identified even if the are in a cluster, while the rest of image is considered to be a part of the background. The morphological segmentation makes it possilbe to calculate outstanding feature that could not be obtain by simple observation. These are passed to a fuzzy classifier which decides the probability of the biopsy to belong to a high or low cancer level. Obtaining these measures by human observation is a hard, and nonprecise task. The extracted features will make it possible to reach a parametric classification that is more efficient than the subjective classification made by a human observation
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