Yap, MH and Ng, CC and Chatwin, K and Abbott, CA and Bowling, FL and Boulton, AJ and Reeves, Neil D (2016) Computer Vision Algorithms in the Detection of Diabetic Foot Ulceration : A New Paradigm for Diabetic Foot Care? Journal of Diabetes Science and Technology, 10 (2). pp. 612-613. ISSN 1932-2968
Full text not available from this repository.Abstract
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. To implement this novel approach over time, however, photographs of the foot need to be taken and carefully standardized for key specific conditions—distance of image capture from the foot and orientation of the camera relative to the foot. Using a standard human “manually operated” camera, however, will lead to inconsistency in relation to these conditions, and such errors will likely be exaggerated when different operators are involved across different clinical sites. To increase the reliability of the captured foot image with a view to applying computer vision algorithms for early detection and monitoring of DFUs in the future, we have developed a mobile app for the iPad called “FootSnap” to standardize image capture of the plantar surface of diabetic feet (Figure 1).