عنوان مقاله [English]
Breast cancer is one of the most common cancers among women. Many times, no obvious symptoms were identified in breast cancer patients. Accurate detection of breast cancer at the earliest stage is very much essential to reduce mortality. Mammography has been used as a gold standard for over 40 years in diagnosing breast diseases. In recent years, artificial intelligence systems have been the focus of much attention in preventing the subjective analysis of mammograms and physicians by radiologists and enhancing the accuracy of breast cancer detection. In this study, combining the firefly algorithm and applying appropriate image processing to detect breast cancer in mammographic images has been investigated. In this paper, mammographic images in the DDSM dataset were used. Three performance metrics such as sensitivity, specificity and accuracy (93.4%, 91%, 95%) were used to analyze the detection performance. The proposed work shows better performance when compared to existing work in literature.
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