Master Thesis: Detection of Microscopic Fungi and Yeast in Clinical Samples
Published in VISAPP 2023 , Lisbon, Portugal, 2022
Recommended citation: Paplhám, J.; Franc, V. and Lžičařová, D. (2023). Detection of Microscopic Fungi and Yeast in Clinical Samples Using Fluorescence Microscopy and Deep Learning. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP; ISBN 978-989-758-634-7; ISSN 2184-4321, SciTePress, pages 777-784. DOI: 10.5220/0011616100003417 http://hdl.handle.net/10467/100872
This thesis investigates the use of deep neural networks to detect filamentous fungi and yeast in the clinical samples to simplify the work of the human operator of the Motol Faculty Hospital by filtering out samples that are clearly negative and presenting the operator with only samples suspected of containing the contaminant
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BibTeX:
@conference{visapp23,
author={Jakub Paplhám. and Vojtěch Franc. and Daniela Lžiča\v{r}ová.},
title={Detection of Microscopic Fungi and Yeast in Clinical Samples Using Fluorescence Microscopy and Deep Learning},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP},
year={2023},
pages={777-784},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011616100003417},
isbn={978-989-758-634-7},
issn={2184-4321},
}