DFU-SIAM a Novel Diabetic Foot Ulcer Classification with Deep Learning

Diabetes affects roughly 537 million people in the world, and it is predicted to reach 783 by 2045. Diabetic Foot Ulcer (DFU) a major issue with diabetes that may lead lower limb amputation. The rapid evolution of DFU demands immediate intervention prevent terrible consequences amputation related complications.This research introduces novel approach utilizing deep neural networks machine learning for accurate classification diabetic foot ulcer images. proposed method harnesses cutting-edge capabilities Convolutional Neural Networks (CNN) Vision Image Transformers (ViT) within Siamese Network (SNN) Architecture. By employing similarity learning, model efficiently categorizes images into four distinct classes: None, Infection, Ischemia, or Both. training process involves use DFU2021 dataset, all ethical clearances duly obtained. Notably, exhibits remarkable performance on both validation test data, indicating significant breakthrough field disease image classification. potential this innovative extends beyond classification; holds promise as an integral component comprehensive detection tool longitudinal treatment protocol disease.