Detection of Diabetic Foot Ulcer Using Machine/Deep Learning

Diabetic foot ulcer (DFU) has become a major diabetes problem nowadays. It can lead to amputation of the foot if not treated well or on time. DFU treatment is a large-scale problem of health care which results in a high mortality rate. Techniques for early prevention could help save a diabetic patient’s life and prevent disease. DFU analysis and recognition using image-based algorithms of machine learning is an emerging area of research. This chapter presents a review of existing methods and mainly focuses on the approaches of pre-processing, segmentation, detection, and recognition of DFU using handcrafted and deep machine learning methods with their challenges and research gaps. To this end, different methods of image pre-processing, image segmentation, hand-crafted, and deep features extraction, deep features selection, and classification have been studied and analyzed. This systemic review provides assistance for researchers initiating work in this domain to understand easily the detection challenges of DFU.