System Design for Image Segmentation of Skin Lesion Utilizing Deep Learning Techniques

Abstract

The detection and segmentation of skin lesions play a crucial role in the early diagnosis of skin diseases, including melanoma, which is one of the most aggressive forms of skin cancer. Accurate segmentation of skin lesions in dermoscopic images can significantly improve the performance of diagnostic systems. This paper proposes a deep learning-based system designed for the segmentation of skin lesions in medical images. The system utilizes Convolutional Neural Networks (CNNs) and advanced architectures like U-Net, known for their effectiveness in image segmentation tasks. The model processes dermoscopic images by automatically identifying and segmenting the lesions from surrounding skin tissues, overcoming the challenges posed by varying lighting, skin tones, and lesion boundaries.