Skin cancer detection using dermoscopic images with convolutional neural network

Skin malignant melanoma is a high-risk tumor with low incidence but high mortality rates. Early detection and treatment are crucial for a cure. Machine learning studies have focused on classifying melanoma tumors, but these methods are cumbersome and fail to extract deeper features. This limits their ability to distinguish subtle variations in skin lesions accurately, hindering effective early diagnosis. The study introduces a deep learning-based network specifically designed for skin lesion detection to enhance data in the melanoma dataset. It leverages a novel FCDS-CNN architecture to address class-imbalanced problems and improve data quality. Specifically, FCDS-CNN incorporates data augmentation and class…