Abstract
This study introduces an automated wound tissue segmentation algorithm utilizing deep learning models, including UNet base models, trained on a dataset of wound image. Among the models, Attention UNet demonstrated superior performance with the highest sensitivity (0.622) and Dice score (0.608), enabling precise segmentation of wound tissues and providing a robust tool for clinical wound assessment and monitoring.