no code implementations • 25 Apr 2023 • Imran Chowdhury Dipto, Bill Cassidy, Connah Kendrick, Neil D. Reeves, Joseph M. Pappachan, Vishnu Chandrabalan, Moi Hoon Yap
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 networks.
no code implementations • 24 Apr 2023 • Connah Kendrick, Bill Cassidy, Neil D. Reeves, Joseph M. Pappachan, Claire O'Shea, Vishnu Chandrabalan, Moi Hoon Yap
The Diabetic Foot Ulcer Challenge 2022 focused on the task of diabetic foot ulcer segmentation, based on the work completed in previous DFU challenges.
1 code implementation • 22 Apr 2022 • Connah Kendrick, Bill Cassidy, Joseph M. Pappachan, Claire O'Shea, Cornelious J. Fernandez, Elias Chacko, Koshy Jacob, Neil D. Reeves, Moi Hoon Yap
This paper demonstrates that image processing using refined contour as ground truth can provide better agreement with machine predicted results.
no code implementations • 1 Jan 2022 • Moi Hoon Yap, Connah Kendrick, Neil D. Reeves, Manu Goyal, Joseph M. Pappachan, Bill Cassidy
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.
no code implementations • 19 Nov 2021 • Bill Cassidy, Connah Kendrick, Neil D. Reeves, Joseph M. Pappachan, Claire O'Shea, David G. Armstrong, Moi Hoon Yap
Diabetic foot ulcer classification systems use the presence of wound infection (bacteria present within the wound) and ischaemia (restricted blood supply) as vital clinical indicators for treatment and prediction of wound healing.
no code implementations • 17 May 2021 • Bill Cassidy, Neil D. Reeves, Joseph M. Pappachan, Naseer Ahmad, Samantha Haycocks, David Gillespie, Moi Hoon Yap
This research proposes a mobile and cloud-based framework for the automatic detection of diabetic foot ulcers and conducts an investigation of its performance.
no code implementations • 7 Apr 2021 • Moi Hoon Yap, Bill Cassidy, Joseph M. Pappachan, Claire O'Shea, David Gillespie, Neil Reeves
We describe the data preparation of DFUC2021 for ground truth annotation, data curation and data analysis.