Skin Lesion Detection: A Survey of Recent Breakthrough

Abstract

Melanoma, a highly aggressive form of skin cancer, continues to rise in prevalence worldwide. Early identification of skin lesions is crucial for enhancing patient prognosis and minimizing medical expenses. Automated detection systems have emerged as essential tools in dermatology, improving diagnostic precision and efficiency. This paper explores recent advancements in skin lesion analysis, covering both conventional machine learning techniques and state-of-the-art deep learning architectures. Additionally, it discusses existing obstacles and potential future research directions in this field.