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Diabetic Foot Ulcer Grand Challenge 2022 Summary

arXiv 2304.12001 ↗First posted 24 Apr 2023cs.CVcited by 0

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Abstract (arXiv)

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 images of full-view foot ulcer images together with corresponding delineation of ulcer regions. This paper provides an overview of the challenge, a summary of the methods proposed by the challenge participants, the results obtained from each technique, and a comparison of the challenge results. The best-performing network was a modified HarDNet-MSEG, with a Dice score of 0.7287.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 24 of its 29 references that are in the map. First posted on arXiv 24 Apr 2023.

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References · 24

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12 more
  1. 2019The VIA Annotation Software for Images, Audio and Videocited by 167
  2. 2021HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPScited by 71
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  6. 2019Recognition of Ischaemia and Infection in Diabetic Foot Ulcers: Dataset and Techniquescited by 19
  7. 2020Deep Learning in Diabetic Foot Ulcers Detection: A Comprehensive Evaluationcited by 19
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  10. 2020Multiclass Wound Image Classification using an Ensemble Deep CNN-based Classifiercited by 9
  11. 2021A Cloud-based Deep Learning Framework for Remote Detection of Diabetic Foot Ulcerscited by 7
  12. 2022Development of Diabetic Foot Ulcer Datasets: An Overviewcited by 3

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