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.本数据集包含用于皮肤病变二分类的皮肤镜图像（dermoscopic images），可将病变分为良性（Benign）与恶性（Malignant）两类。本数据集旨在为自动化皮肤癌检测、医学图像分析以及基于深度学习的诊断系统相关研究提供支撑。数据集内含经过清理与规整的皮肤镜图像，适用于机器学习模型的训练、验证与评估工作。最终数据集共计收录6482张图像，其中良性样本3404份，恶性样本3078份。所有图像均取自公开的皮肤病学图像资源，并经过去重、标签校验与质量过滤等预处理步骤，以提升数据集的一致性与可靠性。本数据集仅可用于计算机辅助诊断（computer-aided diagnosis）、皮肤癌分类以及皮肤病学领域人工智能应用相关的研究工作。