U-Net in Histological Segmentation: Comparison of the Effect of Using Different Color Spaces and Final Activation Functions

László Körmöczi; László Nyúl

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Paper

U-Net in Histological Segmentation: Comparison of the Effect of Using Different Color Spaces and Final Activation Functions

Topics: Applications of Machine Learning; Biomechanical Imaging; Deep Learning in Bioimaging; Histology and Tissue Imaging; Image Processing Methods; Quantitative Bioimaging

In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING, 386-389, 2025 , Porto, Portugal

Authors: László Körmöczi and László Nyúl

Affiliation: Department of Image Processing and Computer Graphics, University of Szeged, Szeged, Hungary

Keyword(s): Semantic Segmentation, U-Net, Machine Learning, Deep Learning, Color Space Conversion.

Abstract: Deep neural networks became widespread in numerous fields of image processing, including semantic segmentation. U-Net is a popular choice for semantic segmentation of microscopy images, e.g. histological sections. In this paper, we compare the performance of a U-Net architecture in three different color spaces: the commonly used, perceptually uniform sRGB, the perceptually uniform but device-independent CIE L*a*b*, and linear RGB color space that is uniform in terms of light intensity. Furthermore, we investigate the network’s performance on data combinations that were unseen during training.

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Paper citation in several formats:

Körmöczi, L. and Nyúl, L. (2025). U-Net in Histological Segmentation: Comparison of the Effect of Using Different Color Spaces and Final Activation Functions. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOIMAGING; ISBN 978-989-758-731-3; ISSN 2184-4305, SciTePress, pages 386-389. DOI: 10.5220/0013323300003911

@conference{bioimaging25,
author={László Körmöczi and László Nyúl},
title={U-Net in Histological Segmentation: Comparison of the Effect of Using Different Color Spaces and Final Activation Functions},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOIMAGING},
year={2025},
pages={386-389},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013323300003911},
isbn={978-989-758-731-3},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOIMAGING
TI - U-Net in Histological Segmentation: Comparison of the Effect of Using Different Color Spaces and Final Activation Functions
SN - 978-989-758-731-3
IS - 2184-4305
AU - Körmöczi, L.
AU - Nyúl, L.
PY - 2025
SP - 386
EP - 389
DO - 10.5220/0013323300003911
PB - SciTePress