Objective:Image segmentation of chronic wounds is one of the keys to wound care,and different degrees of injury and surrounding skin will increase the difficulty of segmentation.In this study,a fast and accurate segmentation and recognition method for chronic foot wounds based on artificial intelligence algorithm was constructed to assist wound care.Methods:The images were labeled firstly,and then deep learning was used for image segmentation training.Two datasets were trained,in which the foot ulcer segmentation challenge was evaluated using intersection-ratio(IOU)related indicators,and the Medetec foot ulcer-224 dataset was evaluated using DICE coefficient.Results:The image segmentation training with this method obtained more accurate.For both data sets,both the training set and the validation set have excellent accuracy.Conclusion:The segmentation method constructed in this paper can be used for the segmentation of chronic foot wounds to achieve accurate image recognition,and has achieved satisfactory segmentation effect,which has certain practical value and reference significance in assisting the application of chronic foot wound nursing and improving the quality of nursing.
NETL
NSTL
万方数据
