Interpreting Venous and Arterial Ulcer Images Through the Grad-CAM Lens: Insights and Implications in CNN-Based Wound Image Classification

Neuwieser H, Jami NVSJ, Meier RJ, Liebsch G, Felthaus O, Klein S, Schreml S, Berneburg M, Prantl L, Leutheuser H, Kempa S (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Diagnostics MDPI

Book Volume: 15

Article Number: 2184

Journal Issue: 17

DOI: 10.3390/diagnostics15172184

Abstract

Background/Objectives: Chronic wounds of the lower extremities, particularly arterial and venous ulcers, represent a significant and costly challenge in medical care. To assist in differential diagnosis, we aim to evaluate various advanced deep-learning models for classifying arterial and venous ulcers and visualize their decision-making processes. Methods: A retrospective dataset of 607 images (198 arterial and 409 venous ulcers) was used to train five convolutional neural networks: ResNet50, ResNeXt50, ConvNeXt, EfficientNetB2, and EfficientNetV2. Model performance was assessed using accuracy, precision, recall, F1-score, and ROC-AUC. Grad-CAM was applied to visualize image regions contributing to classification decisions. Results: The models demonstrated high classification performance, with accuracy ranging from 72% (ConvNeXt) to 98% (ResNeXt50). Precision and recall values indicated strong discrimination between arterial and venous ulcers, with EfficientNetV2 achieving the highest precision. Conclusions: AI-assisted classification of venous and arterial ulcers offers a valuable method for enhancing diagnostic efficiency.

Involved external institutions

Universität Bayreuth DE Germany (DE) PreSens Precision Sensing GmbH DE Germany (DE) Universitätsklinikum Regensburg DE Germany (DE)

How to cite

APA:

Neuwieser, H., Jami, N.V.S.J., Meier, R.J., Liebsch, G., Felthaus, O., Klein, S.,... Kempa, S. (2025). Interpreting Venous and Arterial Ulcer Images Through the Grad-CAM Lens: Insights and Implications in CNN-Based Wound Image Classification. Diagnostics, 15(17). https://doi.org/10.3390/diagnostics15172184

MLA:

Neuwieser, Hannah, et al. "Interpreting Venous and Arterial Ulcer Images Through the Grad-CAM Lens: Insights and Implications in CNN-Based Wound Image Classification." Diagnostics 15.17 (2025).

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