Abstract
Here, we introduce YeastMate, a user-friendly deep learning-based application for automated detection and segmentation of Saccharomyces cerevisiae cells and their mating and budding events in microscopy images. We build upon Mask R-CNN with a custom segmentation head for the subclassification of mother and daughter cells during lifecycle transitions. YeastMate can be used directly as a Python library or through a standalone application with a graphical user interface (GUI) and a Fiji plugin as easy-to-use frontends.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Biologie |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften; Biologie |
ISSN: | 1367-4803 |
Sprache: | Englisch |
Dokumenten ID: | 113069 |
Datum der Veröffentlichung auf Open Access LMU: | 02. Apr. 2024, 07:44 |
Letzte Änderungen: | 02. Apr. 2024, 07:44 |