Detection of Melanoma in Skin Images using Convolutional Neural Networks

Skin cancer is one of the most common types of cancer, affecting millions throughout the world. It is primarily caused by overexposure to ultraviolet (UV) light from the sun or artificial sources. Melanoma is the most aggressive and life-threatening kind of cancer because of its high metastatic potential. Early identification is vital in lowering mortality rates. Traditional diagnostic approaches, such as eye examination and biopsy, are timeconsuming and subjective. Recent advances in deep learning and computer vision show promise for automated skin cancer screening. Specifically, Convolutional Neural Networks(CNNs) have demonstrated high accuracy in classifying skin lesions from dermoscopic images. CNNs leverage hierarchical feature extraction, making them well-suited for recognizing complex patterns in medical images.