What is a wound healing scratch assay?
A wound healing scratch assay is an in vitro cell migration experiment. A confluent cell monolayer is scratched to create a cell-free gap, then images are captured over time to estimate how quickly cells migrate into the open area.
The key image-analysis task is to separate the wound region from the cell-covered region, inspect the segmentation mask, and report reproducible measurements.
Which measurements matter?
Wound area percentage
Wound area percentage describes how much of the image field is still open. It is intuitive and commonly reported, but it can be sensitive to crop choices, circular microscope fields, labels, and black borders.
Mean horizontal gap width
Gap width summarizes the wound span across image rows. It is useful when crop or field-of-view differences make area fractions harder to compare. Cytomove reports mean, median, spread, valid rows, and QC warnings so the area and width metrics can be read together.
A reliable workflow should not hide the mask. Researchers need to see where the segmentation boundary is, adjust settings when needed, and document the export used for reporting.
A browser-based analysis workflow
- Open one scratch assay image, or drop multiple time-point images to create a group.
- Select a brightfield or phase contrast preset and review the contour or mask.
- Adjust threshold, variance radius, field crop, orientation, or rotation if needed.
- Use manual correction tools for difficult regions, debris, or missed wound fragments.
- Export PNG overlays, group PNG ZIPs, plots, CSV, or Excel-compatible tables.
How does this relate to ImageJ workflows?
Many wound healing assays are still analyzed with ImageJ macros or manual workflows. Cytomove is designed to complement that familiar approach with a local browser workspace: fast visual review, exportable measurements, and a clear record of the settings used for each image.
Validation against manual and ImageJ-style references is still in progress, so Cytomove should be treated as a prototype feedback tool rather than a final public beta.
What does browser-local image handling mean?
You can open image files normally through the file picker or drag-and-drop. The current web workflow analyzes those files in the browser and keeps assay image files on your device. This is important for unpublished microscopy data and early-stage academic workflows.
Supported exports
Cytomove currently focuses on practical outputs for review and reporting: overlay PNGs, group overlay ZIP files, area and width plot ZIP files, CSV metrics, and Excel-compatible tables.
Ready to test a scratch assay image?
Use the browser workspace for a quick local review.