Vacuolar Phenotype Analyzer: a trained CNN model and analysis pipeline for yeast vacuolar phenotypes.

The Vacuolar Phenotype Analyzer model uses a convolutional neural network (CNN) to detect individual yeast cells in confocal FM4-64 images and classify each cell into vacuolar phenotypes A, B, or C, representing different degrees of vacuolar fragmentation.

If you use this model or code, please cite this work.

Keywords

Confocal microscopy, Microscopy, Vacuoles, Vacuoles/classification, FM4-64, Vacuoles/physiology, Saccharomyces cerevisiae, Yeast

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

Found an issue? Give us feedback

0

Average