Advancements in Diabetic Foot Ulcer Detection: A Thermal Imaging Approach

Diabetes, a chronic disease affecting millions worldwide, often leads to neuropathy, causing insensitivity in the feet. This condition increases the risk of Diabetic Foot Ulcers (DFUs), which, if left unnoticed, may result in the need for amputation. To address this critical issue, we propose a novel diagnostic approach utilizing a prototype scanner equipped with a thermal camera. The thermal camera captures images of the plantar region, presenting a distinct rainbow color pattern. High temperatures are represented by the color red, indicating potential infection, while green signifies moderate or normal temperatures. Cooler regions are represented by blue or purple hues. Leveraging deep learning, our model is trained on the pixel values extracted from these thermal images. This comprehensive dataset enables the accurate detection of DFUs by analyzing temperature variations in the plantar region. By utilizing this innovative scanner, healthcare professionals can swiftly and non-invasively identify potential ulcers. Early detection allows for timely intervention and treatment, minimizing the risk of complications and the need for amputation. This research presents a promising avenue for improving the management of diabetic complications, enhancing patient outcomes, and reducing the burden associated with DFUs.