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BURGET, R. ČIČATKA, M. LÁNCOŠ, J.
Originální název
From Segmentation to Clustering: Advancing Algorithms for Grouping Microbial Colonies on Agar Plates
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Agar plates are essential in microbiology, yet manual intervention remains common for tasks like colony-picking, especially in smaller laboratories. This paper addresses the research gap of clustering microbes within agar plate images to advance automated solutions. Three innovative clustering approaches based on visual properties are presented. Using synthetic agar plate images with annotated microbes, these algorithms are developed and evaluated, with performance assessed using the V-measure metric. Results reveal challenges in pixel-level clustering without segmentation masks (V-measure: 0.284), while U-Net autoencoder features with OPTICS show reasonable performance (V-measure: 0.705). K-means with a colony extraction pipeline excels (V-measure: 0.942), emphasizing the importance of high-level colony features. These solutions offer potential enhancements for colony-picking robots and advanced analysis. This research significantly contributes to agar plate analysis, paving the way for future automated colony analysis and streamlined lab workflows.
Klíčová slova
Image segmentation;Visualization;Microbiology;Pipelines;Clustering algorithms;Feature extraction;Optics
Autoři
BURGET, R.; ČIČATKA, M.; LÁNCOŠ, J.
Vydáno
30. 10. 2023
Místo
Ghent
ISBN
979-8-3503-9328-6
Kniha
2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)
Strany od
176
Strany do
181
Strany počet
6
BibTex
@inproceedings{BUT185241, author="Radim {Burget} and Michal {Čičatka} and Jan {Láncoš}", title="From Segmentation to Clustering: Advancing Algorithms for Grouping Microbial Colonies on Agar Plates", booktitle="2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)", year="2023", pages="176--181", address="Ghent", isbn="979-8-3503-9328-6" }