01738nas a2200241   4500000000100000000000100001008004100002260001200043653002200055653001400077653001800091653002900109653002300138653002300161100002100184700002000205245008900225856009700314300001100411490000600422520105400428022001401482       2019                            d  c06/201910aFeature Selection10aMammogram10aBreast Cancer10aComputer Aided Detection10aImmune Recognition10aFuzzy Segmentation1 aHamdadou Djamila1 aLeila Belkhodja00aIMCAD: Computer Aided System for Breast Masses Detection based on Immune Recognition  uhttps://www.ijimai.org/journal/sites/default/files/files/2018/12/ijimai_5_5_12_pdf_14881.pdf  a97-1080 v53 aComputer Aided Detection (CAD) systems are very important tools which help radiologists as a second reader in detecting early breast cancer in an efficient way, specially on screening mammograms. One of the challenging problems is the detection of masses, which are powerful signs of cancer, because of their poor apperance on mammograms. This paper investigates an automatic CAD for detection of breast masses in screening mammograms based on fuzzy segmentation and a bio-inspired method for pattern recognition: Artificial Immune Recognition System. The proposed approach is applied to real clinical images from the full field digital mammographic database: Inbreast. In order to validate our proposition, we propose the Receiver Operating Characteristic Curve as an analyzer of our IMCAD classifier system, which achieves a good area under curve, with a sensitivity of 100% and a specificity of 95%. The recognition system based on artificial immunity has shown its efficiency on recognizing masses from a very restricted set of training regions.  a1989-1660