Binary_Skin_Cancer_Dataset

This dataset contains dermoscopic images for binary skin lesion classification into Benign and Malignant categories. It was curated to support research in automated skin cancer detection, medical image analysis, and deep learning-based diagnostic systems. The dataset includes cleaned and organized dermoscopic images suitable for training, validation, and evaluation of machine learning models.
The final dataset contains 6482 images, including 3404 benign and 3078 malignant samples. The images were curated from publicly available dermatology image sources, and preprocessing steps such as duplicate removal, label checking, and quality filtering were applied to improve dataset consistency and reliability.
This dataset is intended for research purposes in computer-aided diagnosis, skin cancer classification, and AI applications in dermatology.