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The classification and the count of white blood cells in microscopy images allows the in vivo assessment of a wide range of important hematic pathologies (i.e., from presence of infections to leukemia). Nowadays, the morphological cell classification is typically made by experienced operators. Such a procedure presents undesirable drawbacks: slowness and it presents a not standardized accuracy since it depends on the operator's capabilities and tiredness. Only few attempts of partial/full automated systems based on image-processing systems are present in literature and they are still at prototype stage. This paper presents a methodology to achieve an automated detection and classification of leucocytes by microscope color images. The proposed system firstly individuates in the blood image the leucocytes from the others blood cells, then it extracts morphological indexes and finally it classifies the leucocytes by a neural classifier in Basophil, Eosinophil, Lymphocyte, Monocyte and Neutrophil.
Piuri et al. (Fri,) studied this question.