233 citations · 479 across the 11 of their papers we have counts for
12 papers
Quantifying the Effect of Image Similarity on Diabetic Foot Ulcer Classification
Imran Chowdhury Dipto, Bill Cassidy, Connah Kendrick +4
This research conducts an investigation on the effect of visually similar images within a publicly available diabetic foot ulcer dataset when training deep learning classification…
Diabetic Foot Ulcer Grand Challenge 2022 Summary
Connah Kendrick, Bill Cassidy, Neil D. Reeves +4
The Diabetic Foot Ulcer Challenge 2022 focused on the task of diabetic foot ulcer segmentation, based on the work completed in previous DFU challenges. The challenge provided 4000…
Translating Clinical Delineation of Diabetic Foot Ulcers into Machine Interpretable Segmentation
Connah Kendrick, Bill Cassidy, Joseph M. Pappachan +6
Diabetic foot ulcer is a severe condition that requires close monitoring and management. For training machine learning methods to auto-delineate the ulcer, clinical staff must prov…
Development of Diabetic Foot Ulcer Datasets: An Overview
Moi Hoon Yap, Connah Kendrick, Neil D. Reeves +3
This paper provides conceptual foundation and procedures used in the development of diabetic foot ulcer datasets over the past decade, with a timeline to demonstrate progress. We c…
Diabetic Foot Ulcer Grand Challenge 2021: Evaluation and Summary
Bill Cassidy, Connah Kendrick, Neil D. Reeves +4
Diabetic foot ulcer classification systems use the presence of wound infection (bacteria present within the wound) and ischaemia (restricted blood supply) as vital clinical indicat…
A Cloud-based Deep Learning Framework for Remote Detection of Diabetic Foot Ulcers
Bill Cassidy, Neil D. Reeves, Joseph M. Pappachan +4
This research proposes a mobile and cloud-based framework for the automatic detection of diabetic foot ulcers and conducts an investigation of its performance. The system uses a cr…