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Mitochondria are involved in a variety of cellular functions, which are related to their morphology. The disturbance in mitochondria dynamics has been associated to biomarkers for assessing breast cancer. In this work, we present a method for classification of mitochondrial morphology images, the set of images belongs to cell lines: (MCF10A, BT549, MDAMB23 y CMF) which are subtypes of breast cancer. The proposed method is based on the following image processing algorithms: segmentation (Otsu’s method), features extraction (based on graph measures), and clustering algorithm (K-means). The study reveals a remarkable difference between the graph measures applied in features extraction. We obtain an accuracy of 63.33

Clasificación de imágenes de redes mitocondriales asociadas al estudio del cáncer de mama