Artificial immune recognition system for mammographic mass classification

Nowadays, breast cancer is very frequent among women. Early detection remains the only way to prevent this deadly disease and mammography is one of the most useful screening methods since the use of biopsy is unnecessary in most cases. In this paper, we propose a bio-inspired immunological approach for the classification of mammographic mass to distinguish malignant tumors from benign ones for computer-supported diagnosis. Our three classifiers are based on the artificial immune recognition algorithms AIRS1, AIRS2 and Parallel AIRS which represent three versions of the original Artificial Immune Recognition System AIRS. The obtained results are very promising and encourage the use of bio-inspired immunological approaches for medical data processing.