Wound Image

Wound image analysis is a rapidly developing field focused on using computer vision to improve wound diagnosis, monitoring, and treatment. Current research emphasizes automated wound segmentation and classification using deep learning models, such as U-Net, its variants, and transformer architectures, often incorporating techniques like multi-modal data fusion (combining image and location data) and illumination correction to enhance accuracy. This work is driven by the need for objective, efficient, and accessible wound assessment, particularly for chronic wounds like diabetic foot ulcers, impacting both clinical practice and the development of improved patient care strategies. The availability of large, diverse datasets, including those representing under-represented skin tones, is crucial for advancing these methods.