Team
CytoCV Team
Built by the UW Bothell School of STEM SEE Lab engineering team in collaboration with the University of Utah Miller Lab biology team.
View CytoCV TeamDeveloped at the University of Washington Bothell in collaboration with researchers from the Miller Lab at the University of Utah School of Medicine
CytoCV: Automated Cell Image Analysis for Research Workflows
CytoCV helps researchers upload supported .dv, .tif, and .tiff microscopy stacks, segment individual yeast cells, and review software-generated cell-level measurements through a browser-based workflow. It brings validation, preprocessing, segmentation, review, and export together so experiments are easier to analyze and compare.
University of Washington Bothell
School of STEM
School of Science, Technology, Engineering & Mathematics
Department of Computing & Software Systems
About
About CytoCV
CytoCV is a web-based research workflow for DeltaVision microscopy of yeast cells. It keeps validation, segmentation, measurement, and review connected in one place so imaging results are easier to analyze, compare, and interpret.
See About pageWORKFLOW
From Upload to Export
See how CytoCV guides users through upload, validation, preprocessing, segmentation, measurement, review, and export.
View WorkflowMEASUREMENTS
Cell-Level Research Outputs
Review the software-generated cell-level measurements CytoCV reports for each segmented yeast cell.
View MeasurementsIMAGE INPUT
Built for DeltaVision Yeast Images
CytoCV is designed around DeltaVision yeast imaging workflows that use the logical roles `DIC`, `Blue`, `Red`, and `Green`, often mapped from biology-facing names such as DAPI, mCherry, and GFP.
View Image InputsRESULTS
Review Segmentation and Export Data
Users can inspect segmented cells, review overlays, compare calculated measurements, and export results for downstream analysis.
View ResultsDOCUMENTATION
Using CytoCV
Find upload requirements, workflow guidance, output explanations, and troubleshooting notes.
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