Lymphocite segmentation using mixture of Gaussians and the transferable belief model.
Résumé
In the context of several pathologies, the presence of lym- phocytes has been correlated with disease outcome. The ability to au- tomatically detect lymphocyte nuclei on histopathology imagery could potentially result in the development of an image based prognostic tool. In this paper we present a method based on the estimation of a mixture of Gaussians for determining the probability distribution of the princi- pal image component. Then, a post-processing stage eliminates regions, whose shape is not similar to the nuclei searched. Finally, the Transfer- able Belief Model is used to detect the lymphocyte nuclei, and a shape based algorithm possibly splits them under an equal area and an eccen- tricity constraint principle.
Domaines
Automatique / Robotique
Origine : Fichiers produits par l'(les) auteur(s)
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