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 |
|---|---|
| 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 |
