A new 1,459-image diabetic foot ulcer dataset with visual expert labels enables binary classifiers that reach 90% accuracy for ischaemia and 73% for infection, with ensemble CNNs outperforming handcrafted features.
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Recognition of Ischaemia and Infection in Diabetic Foot Ulcers: Dataset and Techniques
A new 1,459-image diabetic foot ulcer dataset with visual expert labels enables binary classifiers that reach 90% accuracy for ischaemia and 73% for infection, with ensemble CNNs outperforming handcrafted features.