Early Detection of Diabetic Foot Ulcer Using Convolutional Neural Networks
TENSYMP 2021 - 2021 IEEE Region 10 Symposium
Diabetic Foot Ulcer is a very common problem that faces diabetic patients with almost 15 percent of these patients developing a foot ulcer at least once in their life. Diabetic patients tend to suffer from numbness and loss of sensation in their feet making it hard for them to self-detect the ulcer therefore an early detection method is needed. The approach conducted in this paper uses a 2-dimentional image as an input and using convolutional neural networks to analyze the images. The system will classify the input images into two states, no ulcer or the ulcer is present and in this case the location of the ulcer will be marked on the image. The system achieved an F1- score of 81.3% with an improvement of more than 7% from the F1-score achieved in the Diabetic Foot Ulcer Challenge 2020.
Open Access Status
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