Afnan M. Alhassan*
CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2207-2223, 2024, DOI:10.32604/cmc.2024.046427
Abstract Breast Arterial Calcification (BAC) is a mammographic decision dissimilar to cancer and commonly observed in elderly women. Thus identifying BAC could provide an expense, and be inaccurate. Recently Deep Learning (DL) methods have been introduced for automatic BAC detection and quantification with increased accuracy. Previously, classification with deep learning had reached higher efficiency, but designing the structure of DL proved to be an extremely challenging task due to overfitting models. It also is not able to capture the patterns and irregularities presented in the images. To solve the overfitting problem, an optimal feature set has been formed by Enhanced Wolf… More >
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