Name
Abstract | ||
|---|---|---|
There has been a substantial amount of research involving computer methods and technology for the detection and recognition of diabetic foot ulcers (DFUs), but there is a lack of systematic comparisons of state-of-the-art deep learning object detection frameworks applied to this problem. DFUC2020 provided participants with a comprehensive dataset consisting of 2,000 images for training and 2,000 images for testing. This paper summarizes the results of DFUC2020 by comparing the deep learning-based algorithms proposed by the winning teams: Faster R-CNN, three variants of Faster R-CNN and an ensemble method; YOLOv3; YOLOv5; EfficientDet; and a new Cascade Attention Network. For each deep learning method, we provide a detailed description of model architecture, parameter settings for training and additional stages including pre-processing, data augmentation and post-processing. We provide a comprehensive evaluation for each method. All the methods required a data augmentation stage to increase the number of images available for training and a post-processing stage to remove false positives. The best performance was obtained from Deformable Convolution, a variant of Faster R-CNN, with a mean average precision (mAP) of 0.6940 and an F1-Score of 0.7434. Finally, we demonstrate that the ensemble method based on different deep learning methods can enhance the F1-Score but not the mAP. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.compbiomed.2021.104596 | COMPUTERS IN BIOLOGY AND MEDICINE |
Keywords | DocType | Volume |
Diabetic foot ulcers, Object detection, Machine learning, Deep learning, DFUC2020 | Journal | 135 |
ISSN | Citations | PageRank |
0010-4825 | 1 | 0.37 |
References | Authors | |
0 | 21 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Moi Hoon Yap | 1 | 190 | 27.82 |
| Ryo Hachiuma | 2 | 4 | 4.82 |
| Azadeh Alavi | 3 | 1 | 0.37 |
| Raphael Brüngel | 4 | 1 | 1.72 |
| Manu Goyal | 5 | 1 | 0.37 |
| Hongtao Zhu | 6 | 1 | 0.37 |
| Bill Cassidy | 7 | 1 | 0.37 |
| Johannes Ruckert | 8 | 1 | 0.37 |
| Moshe Olshansky | 9 | 1 | 0.37 |
| Xiaojun Huang | 10 | 4 | 1.45 |
| Hideo Saito | 11 | 1147 | 169.63 |
| Saeed Hassanpour | 12 | 52 | 10.54 |
| Christoph M. Friedrich | 13 | 186 | 25.44 |
| David Ascher | 14 | 1 | 0.37 |
| Anping Song | 15 | 1 | 0.37 |
| Hiroki Kajita | 16 | 1 | 0.37 |
| David Gillespie | 17 | 1 | 0.37 |
| Neil D. Reeves | 18 | 15 | 2.52 |
| Joseph Pappachan | 19 | 1 | 1.04 |
| Claire O'Shea | 20 | 1 | 1.04 |
| Eibe Frank | 21 | 1 | 0.37 |