Multilabel Classification of Otoscopy Images in Deep Learning for Detailed Assessment of Eardrum Condition

Antoine Perry, Ilaria Renna, Florence Rossant, Nicolas Wallaert

2025

Abstract

This study presents a ResNet50-based CNN framework for multi-label classification of eardrum images, focusing on a detailed diagnosis of otologic disorders. Unlike prior studies centered on common pathologies, our approach explores less common eardrum conditions using a dataset of 4836 images annotated by two audiologists. The model effectively identifies various pathologies and conditions that can coexist in clinical practice, with a Jaccard score of 0.84, indicating a high level of agreement with the annotations made by an expert. This score notably exceeds the interoperator agreement (0.69) between the two audiologists. This demonstrates the model’s accuracy but also its potential as a reliable tool for clinical diagnosis.

Paper Citation

in Harvard Style

Perry A., Renna I., Rossant F. and Wallaert N. (2025). Multilabel Classification of Otoscopy Images in Deep Learning for Detailed Assessment of Eardrum Condition. In Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-730-6, SciTePress, pages 794-800. DOI: 10.5220/0013316700003905

in Bibtex Style

@conference{icpram25,
author={Antoine Perry and Ilaria Renna and Florence Rossant and Nicolas Wallaert},
title={Multilabel Classification of Otoscopy Images in Deep Learning for Detailed Assessment of Eardrum Condition},
booktitle={Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2025},
pages={794-800},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013316700003905},
isbn={978-989-758-730-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Multilabel Classification of Otoscopy Images in Deep Learning for Detailed Assessment of Eardrum Condition
SN - 978-989-758-730-6
AU - Perry A.
AU - Renna I.
AU - Rossant F.
AU - Wallaert N.
PY - 2025
SP - 794
EP - 800
DO - 10.5220/0013316700003905
PB - SciTePress