A benchmark of seven models and four image preprocessing methods on the CBIS-DDSM mammography dataset reports near-perfect CNN accuracy and up to 13-point transformer gains with HOG/AHE, wrapped in a proposed explainable ensemble called MammoFormer.
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Transformer-Based Explainable Deep Learning for Breast Cancer Detection in Mammography: The MammoFormer Framework
A benchmark of seven models and four image preprocessing methods on the CBIS-DDSM mammography dataset reports near-perfect CNN accuracy and up to 13-point transformer gains with HOG/AHE, wrapped in a proposed explainable ensemble called MammoFormer.