An overview of skin lesion segmentation methods: techniques, challenges, and future directions

Abstract

This study provides an overview of the current skin lesion semantic segmentation work. To identify a melanoma, a dangerous form of skin cancer, skin lesion segmentation techniques are crucial. However, the segmentation of skin lesions is challenging due to the diversity of lesion sizes, colors, shapes, and textures. This review paper presents a detailed examination of the various algorithms and methods that have been proposed for skin lesion segmentation. These methods use different image features, such as pixel intensity, texture, and color, to segment the image into distinct parts. The performance of these algorithms is evaluated and compared, and their strengths and limitations are discussed. This article aims to provide a comprehensive overview of the current state of skin lesion segmentation research, which will help researchers and practitioners better understand the current advancements in this field and identify future research directions.