Computer aided systems for detection and diagnosis on mammograms are one of the automatic solutions that help the radiologist in detecting abnormalities in an efficient way as a second reader of digital mammograms. To this end, we propose, in this paper, a methodology for computeraided detection of breast masses on screening mammograms, which joins multidisciplinary axes such as medical domain, image processing and biological pattern recognition. For this, we focus on minimizing false positive findings and increasing true positive cases using all benefits of fuzzy processing and artificial immune recognition system.
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