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Automatic Classification of Diabetic Foot Ulcer Images - A Transfer-Learning Approach to Detect Wound Maceration

Hüsers J, Hafer G, Heggemann J, Wiemeyer S, Przysucha M, Dissemond J, Moelleken M, Erfurt-Berge C, Hübner U (2022)

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Publication Type: Conference contribution

Publication year: 2022

Journal

Publisher: IOS Press BV

Book Volume: 289

Pages Range: 301-304

Conference Proceedings Title: Studies in Health Technology and Informatics

ISBN: 9781643682501

DOI: 10.3233/SHTI210919

Abstract

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.

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How to cite

APA:

Hüsers, J., Hafer, G., Heggemann, J., Wiemeyer, S., Przysucha, M., Dissemond, J.,... Hübner, U. (2022). Automatic Classification of Diabetic Foot Ulcer Images - A Transfer-Learning Approach to Detect Wound Maceration. In John Mantas, Arie Hasman, Mowafa S. Househ, Parisis Gallos, Emmanouil Zoulias, Joseph Liasko (Eds.), Studies in Health Technology and Informatics (pp. 301-304). IOS Press BV.

MLA:

Hüsers, Jens, et al. "Automatic Classification of Diabetic Foot Ulcer Images - A Transfer-Learning Approach to Detect Wound Maceration." Proceedings of the Studies in Health Technology and Informatics Ed. John Mantas, Arie Hasman, Mowafa S. Househ, Parisis Gallos, Emmanouil Zoulias, Joseph Liasko, IOS Press BV, 2022. 301-304.

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