Smart Wound Measurement: Fusion of Advanced Image Analysis Technique

“Can precise wound detection and dimension analysis revolutionize healthcare management?” This project focuses on improving wound care by using dimension analysis and automated wound detection. In this research, the crucial challenge of wound detection and dimension analysis in healthcare is tackled. To improve patient care outcomes and clinical workflow efficiency, as well as the overall quality and efficiency of healthcare delivery, this difficulty must be addressed. Using techniques from computer vision and deep learning models, the system analyzes and correctly detects wounds from medical photos. To provide a thorough assessment to understand if medical intervention is required or not. This research study uses a two-fold model approach for automated wound detection and evaluation. Two models were employed in the study: initially, the DETR model was utilized, followed by the implementation of the YOLO model for the detection task. After the initial identification of the wound, the method combines contour and Canny edge detection models to concentrate on the wound area and enable an accurate assessment of its dimensions. The final objective is to determine whether the wound needs normal care or whether medical intervention is required which may involve administering a tetanus shot if the wound exceeds a certain threshold. Due to accuracy challenges, the DETR model for wound detection was initially utilized in this study. As a result, the YOLOv8 model was adopted instead, and it showed significant improvements with over 90% accuracy. The area and dimension of the wound are measured for dimension analysis using a combination of contour detection and a canny edge detector. This novel strategy seeks to improve wound care effectiveness by enabling prompt interventions and improving patient satisfaction. The initiative advances the nexus between technology and healthcare by showcasing the potential of automated technologies to enhance clinical procedures in wound care.