A feature fusion system for basal cell carcinoma detection through data‐driven feature learning and patient profile

Basal cell carcinoma (BCC) is the most common skin cancer, which is highly damaging in its advanced stages. Computer‐aided techniques provide a feasible option for early detection of BCC. However, automated BCC detection techniques immensely rely on handcrafting high‐level precise features. Such features are not only computationally complex to design but can also represent a very limited aspect of the lesion characteristics. This paper proposes an automated BCC detection technique that directly learns the features from image data, eliminating the need for handcrafted feature design.