Classification of HER2 Breast Cancer with Ensemble of Fuzzy Decision Trees

In this paper a decision making support system dedicated to histopathology image recognition is considered. The proposed system supports the classification process of histopathology preparations through microscopy image information analysis, with respect to the degree of HER2/neu receptor overexpression. The system combines the output information of ensemble of classifiers – fuzzy decision trees. We propose an aggregation process of the corresponding classifiers results with fuzzy Sugeno integral. What more, we introduce new image fragmentation concept, in order to improve the considered classification process. The proposed approach was tested over real clinical data of HER2 breast cancer histopathology images.

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