Multi-scanner Canine Cutaneous Squamous Cell Carcinoma Histopathology Dataset

Wilm F, Fragoso M, Bertram CA, Stathonikos N, Öttl M, Qiu J, Klopfleisch R, Maier A, Breininger K, Aubreville M (2023)

Publication Type: Conference contribution

Publication year: 2023

Journal

Publisher: Springer Science and Business Media Deutschland GmbH

Pages Range: 206-211

Conference Proceedings Title: Informatik aktuell

Event location: Braunschweig

ISBN: 9783658416560

DOI: 10.1007/978-3-658-41657-7_46

Abstract

In histopathology, scanner-induced domain shifts are known to impede the performance of trained neural networks when tested on unseen data. Multidomain pre-training or dedicated domain-generalization techniques can help to develop domain-agnostic algorithms. For this, multi-scanner datasets with a high variety of slide scanning systems are highly desirable. We present a publicly available multi-scanner dataset of canine cutaneous squamous cell carcinoma histopathology images, composed of 44 samples digitized with five slide scanners. This dataset provides local correspondences between images and thereby isolates the scanner-induced domain shift from other inherent, e.g. morphology-induced domain shifts. To highlight scanner differences, we present a detailed evaluation of color distributions, sharpness, and contrast of the individual scanner subsets. Additionally, to quantify the inherent scanner-induced domain shift, we train a tumor segmentation network on each scanner subset and evaluate the performance both in - and cross-domain. We achieve a class-averaged in-domain intersection over union coefficient of up to 0.86 and observe a cross-domain performance decrease of up to 0.38, which confirms the inherent domain shift of the presented dataset and its negative impact on the performance of deep neural networks.

Authors with CRIS profile

Involved external institutions

University Medical Centre Utrecht (UMC Utrecht) Netherlands (NL) Freie Universität Berlin Germany (DE) Technische Hochschule Ingolstadt Germany (DE) Veterinärmedizinische Universität Wien (Vetmeduni Vienna) / University of Veterinary Medicine, Vienna Austria (AT)

How to cite

APA:

Wilm, F., Fragoso, M., Bertram, C.A., Stathonikos, N., Öttl, M., Qiu, J.,... Aubreville, M. (2023). Multi-scanner Canine Cutaneous Squamous Cell Carcinoma Histopathology Dataset. In Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 206-211). Braunschweig, DE: Springer Science and Business Media Deutschland GmbH.

MLA:

Wilm, Frauke, et al. "Multi-scanner Canine Cutaneous Squamous Cell Carcinoma Histopathology Dataset." Proceedings of the Bildverarbeitung für die Medizin Workshop, BVM 2023, Braunschweig Ed. Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff, Springer Science and Business Media Deutschland GmbH, 2023. 206-211.

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