Real-Time Web Application to Classify Diabetic Foot Ulcer

Diabetic foot ulcers are one of the major complications of type 2 diabetes and can result in gangrene and amputation if left untreated. Early detection and treatment are essential for reducing the risk of amputation. Imaging, such as digital photography or imaging scans, can be a valuable tool in detecting and monitoring diabetic foot ulcers, documenting their size and location, identifying underlying issues, and evaluating treatment effectiveness. This paper utilises a two-dimensional image as its input and applies an ensemble of neural networks to analyse the images. The system is capable of performing image classification into four distinct states, infection, ischaemia, both, and none.