Computer Vision Algorithms in the Detection of Diabetic Foot Ulceration
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Diabetic foot ulcers (DFUs) and other foot pathologies are highly prevalent in people with diabetes, especially in patients with the secondary complications of peripheral neuropathy and/or peripheral vascular disease.1 The development of DFUs involves changes in the appearance of the foot over time, however, many subtle changes in foot shape, texture, and color will likely be undetectable by human vision until a DFU is established. Advanced computer vision algorithms have been applied in the medical field to detect subtle signs to differentiate the type of tumours2 subtle changes in facial features—such as fine wrinkles on the face3 and micro facial movements4—where some of these features are not detectable by human vision. We see the opportunity to apply computer vision algorithms to help in the early detection of key pathological changes in the diabetic foot leading to the development of a DFU.
[1] A. Boulton,et al. The global burden of diabetic foot disease , 2005, The Lancet.
[2] Moi Hoon Yap,et al. A novel algorithm for initial lesion detection in ultrasound breast images , 2008, Journal of applied clinical medical physics.
[3] Nicholas Costen,et al. Micro-Facial Movements: An Investigation on Spatio-Temporal Descriptors , 2014, ECCV Workshops.
[4] Baihua Li,et al. Wrinkle Detection Using Hessian Line Tracking , 2015, IEEE Access.