Classifying Diabetic Foot Ulcers Using Data Augmentation Techniques

Abstract

Abstract: Diabetes is a severe health complication one of which is a Diabetic Foot Ulcer. It is an open sore or wound often observed in diabetic patients who require a careful treatment plan. The most common option is still based on the disease's symptoms and indications because of its large transcendence, which is associated to a higher incidence and expensive and limited diagnostic trials. As a result, the attending physician completes a questionnaire using both its own observation and supporting instrumental measurements (it could be method but not so sure). The above mentioned questionnaire will serve as the basis for the diagnosis, which will also be determined by the consultant's experience and the criteria. Unfortunately, the preceding dependency is unacceptable for some factors, such as the laceration (injury or wound) and location. Therefore, this project is focused on developing a diabetic foot ulcer detection system that helps to identify diabetic foot by developing a suitable feature extraction and classification algorithm. Along with the classification algorithms, the use of Digital image processing techniques helps to improve the quality of images for accurate detection. The number of photos available for training had to be increased with data augmentation for each approach, and false positives had to be eliminated using postprocessing. Hence, with the use of digital image processing techniques, this study aims to establish a new link in the evaluation of the diabetic foot.