ABSTRACT
Blood cells are important parts of our immune system and they protect our body against infections by eliminating viruses, bacteria, parasites and fungi. Types of blood cell are Lymphocytes, Monocytes, Eosinophils and Neutrophils. In this project a computer-aided automated system used that can easily identify and locate blood cell types in blood images has been proposed. Diseases such as bordetella pertussis, hepatitis, viruses, brucella, leukemia increase lymphocytes in the blood whereas diseases such as HIV, rubeola, poliovirus, chickenpox, tuberculosis reduce the amount of lymphocytes. Listeriosis and malaria as well as bacterial and viral infections are some of the diseases that increase the number of monocytes. Allergic diseases, atopic diseases and parasites are factors that increase eosinophil value. Neutrophils show an increase in blood in cases of hormonal causes, metabolic disorders, hemolysis and bleeding. In addition; bacteria, fungi, exotoxin and endotoxin also cause the increase of neutrophils. For classification of these types of blood cells we have used convolutional neural networks (CNN).
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