Smart Point-of-Care Application for Automated Wound Segmentation

The chronic wounds have been a significant public health concern. The continuous monitoring using a smart point-of-care system can improve the chronic wound care quality. The proposed study implements the MobileNetV2 deep learning model for automated wound segmentation and estimates the area. The model has been implemented on a Jetson nano board with integrated camera module for point-of-care system. The model achieves 0.95 dice score for segmentation of images. The advancement could lead to more efficient and accurate chronic wound management, ultimately enhancing patient outcomes.