Automatic Classification of Diabetic Foot Ulcer Images : A Transfer-Learning Approach to Detect Wound Maceration
- Diabetic foot ulcer (DFU) is a chronic wound and a common diabetic complication as 2% – 6% of diabetic patients witness the onset thereof. The DFU can lead to severe health threats such as infection and lower leg amputations, Coordination of interdisciplinary wound care requires well-written but time-consuming wound documentation. Artificial intelligence (AI) systems lend themselves to be tested to extract information from wound images, e.g. maceration, to fill the wound documentation. A convolutional neural network was therefore trained on 326 augmented DFU images to distinguish macerated from unmacerated wounds. The system was validated on 108 unaugmented images. The classification system achieved a recall of 0.69 and a precision of 0.67. The overall accuracy was 0.69. The results show that AI systems can classify DFU images for macerations and that those systems could support clinicians with data entry. However, the validation statistics should be further improved for use in real clinical settings. In summary, this paper can contribute to the development of methods to automatic wound documentation.
Author: | Jens HüsersORCiD, Guido Hafer, Jan Heggemann, Stefan Wiemeyer, Mareike PrzysuchaORCiD, Joachim DissemondORCiD, Maurice MoellekenORCiD, Cornelia Erfurt-BergeORCiD, Ursula Hertha HübnerORCiD |
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Title (English): | Automatic Classification of Diabetic Foot Ulcer Images : A Transfer-Learning Approach to Detect Wound Maceration |
URN: | urn:nbn:de:bsz:959-opus-35870 |
DOI: | https://doi.org/10.3233/SHTI210919 |
ISBN: | 978-1-64368-250-1 |
ISBN: | 978-1-64368-251-8 |
Parent Title (English): | Informatics and Technology in Clinical Care and Public Health |
Publisher: | IOS Press |
Place of publication: | Amsterdam, Berlin, Washington (DC) |
Document Type: | Conference Proceeding |
Language: | English |
Year of Completion: | 2022 |
Release Date: | 2022/08/05 |
First Page: | 301 |
Last Page: | 304 |
Note: | International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH), 16.10. - 17.10.2021, Athens (Greece) |
Faculties: | Fakultät WiSo |
DDC classes: | 600 Technik, Medizin, angewandte Wissenschaften / 610 Medizin, Gesundheit |
Review Status: | Veröffentlichte Fassung/Verlagsversion |
Licence (German): | Creative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International |