PAADARAKSHA - Diabetic Foot Ulcer Detection and Localization Using Deep Learning Techniques

Diabetic foot ulcers (DFU), a potentially life-threatening complication of diabetes, demand proactive mitigation strategies. The exploration delves into the intricate relation- ship between DFU and diabetes, offering a comprehensive remedy for the potentially life-threatening complication. A robust 53- layer Convolutional Neural Network (CNN) categorizes diabetic concerns, followed by meticulous feature analysis via Decision Trees (DT) and Softmax classifiers, exceeding other accuracy, sensitivity, and specificity models. YOLOv8-DFU is a unique localization method that expands on a solid foundation by accurately identifying ischemic or infected regions inside DFU by leveraging YOLOv8's architecture. However, the concept goes beyond simple detection. After painstaking localization, the edge of the ulcer is drawn onto the patient's foot impression, serving as a template for shoemakers to create custom shoes. The customized method represents a major advancement in DFU care, opening the door for preventative measures such as custom-made footwear and enabling prompt diagnostics. The entire approach aims to change how DFU is managed, possibly reducing its terrible effects and enhancing the lives of many diabetics.