Computer-assisted Detection of Lesions in Cystoscopy Continuous Improvement by Data Extension and Model Selection

Eixelberger T, Maisch P, Bolenz C, Wittenberg T (2026)

Publication Type: Conference contribution

Publication year: 2026

Journal

Informatik aktuell Gesellschaft für Informatik (GI)

Publisher: Springer Science and Business Media Deutschland GmbH

Pages Range: 368-374

Conference Proceedings Title: Informatik aktuell

Event location: Lübeck DE

ISBN: 9783658510992

DOI: 10.1007/978-3-658-51100-5_72

Abstract

Bladder cancer is among the most common malignancies, with early detection being critical for effective treatment. This work investigates AI-based lesion detection in cystoscopic images, leveraging both YOLO and visual transformer (VT) architectures. Multiple datasets, including newly collected and publicly available sources, were systematically combined to train and evaluate detection models. Results show that increasing diversity and volume of training data significantly improves detection performance. Pretraining with colonoscopic images further improved model accuracy, indicating similarities in the appearance of lesions across different organs. While VT initially performed better, advanced YOLO outperformed VT with enriched data. These findings highlight the importance of heterogeneous datasets and model selection to advance automated bladder cancer detection.

Authors with CRIS profile

Thomas Eixelberger Chair of Visual Computing (LGDV) Thomas Wittenberg Chair of Visual Computing (LGDV)

Involved external institutions

Universitätsklinikum Ulm DE Germany (DE)

How to cite

APA:

Eixelberger, T., Maisch, P., Bolenz, C., & Wittenberg, T. (2026). Computer-assisted Detection of Lesions in Cystoscopy Continuous Improvement by Data Extension and Model Selection. In Heinz Handels, Katharina Breininger, Thomas Deserno, Andreas Maier, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 368-374). Lübeck, DE: Springer Science and Business Media Deutschland GmbH.

MLA:

Eixelberger, Thomas, et al. "Computer-assisted Detection of Lesions in Cystoscopy Continuous Improvement by Data Extension and Model Selection." Proceedings of the Bildverarbeitung für die Medizin Workshop, BVM 2026, Lübeck Ed. Heinz Handels, Katharina Breininger, Thomas Deserno, Andreas Maier, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff, Springer Science and Business Media Deutschland GmbH, 2026. 368-374.

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