Skin Image

Skin image analysis is a rapidly evolving field focused on improving the accuracy and efficiency of skin disease diagnosis and related applications, such as burn assessment and cosmetic analysis. Current research heavily utilizes deep learning, particularly convolutional neural networks and vision transformers, often incorporating techniques like transfer learning, domain adaptation, and contrastive learning to address challenges posed by limited and imbalanced datasets, diverse skin tones, and the need for interpretable results. These advancements aim to improve diagnostic accuracy, potentially reducing the burden on dermatologists and enabling more equitable access to high-quality care. Furthermore, research is exploring the use of hyperspectral imaging and other advanced imaging modalities to extract richer information from skin images, enhancing diagnostic capabilities.