Detection of Microscopic Fungi and Yeast in Clinical Samples Using Fluorescence Microscopy and Deep Learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00366012" target="_blank" >RIV/68407700:21230/23:00366012 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11130/23:10475689 RIV/00064203:_____/23:10475689
Result on the web
<a href="https://doi.org/10.5220/0011616100003417" target="_blank" >https://doi.org/10.5220/0011616100003417</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0011616100003417" target="_blank" >10.5220/0011616100003417</a>
Alternative languages
Result language
angličtina
Original language name
Detection of Microscopic Fungi and Yeast in Clinical Samples Using Fluorescence Microscopy and Deep Learning
Original language description
Early detection of yeast and filamentous fungi in clinical samples is critical in treating patients predisposed to severe infections caused by these organisms. The patients undergo regular screening, and the gathered samples are manually examined by trained personnel. This work uses deep neural networks to detect filamentous fungi and yeast in the clinical samples to simplify the work of the human operator by filtering out samples that are clearly negative and presenting the operator with only samples suspected of containing the contaminant. We propose data augmentation with Poisson inpainting and compare the model performance against expert and beginner-level humans. The method achieves human-level performance, theoretically reducing the amount of manual labor by 87%, given a true positive rate of 99% and incidence rate of 10%.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
ISBN
978-989-758-634-7
ISSN
2184-4321
e-ISSN
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Number of pages
8
Pages from-to
777-784
Publisher name
SciTePress
Place of publication
Setùbal
Event location
Lisboa
Event date
Feb 19, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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