Wound Healing

Wound healing research focuses on developing objective and efficient methods for assessing and monitoring wound progression, particularly for chronic wounds like diabetic and venous ulcers. Current research employs deep learning models, including convolutional neural networks (CNNs) such as U-Net, ResNet, and EfficientNet, and transformer architectures, to analyze 2D and 3D images (from various sources including consumer-grade videos and ultrasound) for automated wound segmentation, classification (e.g., by type and severity), and healing stage prediction. These advancements aim to improve the accuracy and efficiency of wound care, potentially leading to better treatment strategies and improved patient outcomes by reducing subjectivity and enabling earlier interventions. The integration of body location data with image analysis is also emerging as a promising area.