- Description of the purpose of each step of the image analysis pipeline along with example outputs
- 1. RunStarDist
- 2. OverlayOutlines
- 3. IdentifySecondaryObjects
- 4. IdentifyTertiaryObjects
- 5. Threshold
- 6. Maskobjects
- 7. OverlayOutlines
- 8. Threshold
- 9. Maskobjects
- 10. OverlayOutlines
- 11. Relate Objects
- 12. Overlay Outlines
- 13. Measure Object Intensity
- 14. Measure Colocalization
- 15. Gray to Color
- 16. Overlay Outlines
- 17. Save Images
- 18. Export to Spreadsheet
Uses the StarDist algorithm (https://github.com/stardist/stardist) to segment nuclei
Checks the accuracy of the outlines of the nuclei segmented by RunStarDist
Segments the whole cell outlines
Segments cytoplasm (whole cells minus the nuclei)
Sets the intensity threshold for deeming cells as marker (CD3) positive
Keeps the thresholded areas of the image using a mask and identify the cells present in those areas
Checks the accuracy of detecting CD3+ cells by overlaying the outlines of the CD3+ cells on the grayscale FITC image
Sets the intensity threshold for deeming cells as marker (FoxP3) positive
Keeps the thresholded areas of the image using a mask and identifies the cells/nuclei present in those areas
Checks the accuracy of detecting FoxP3+ cells by overlaying the outlines of the FoxP3+ cells on the grayscale Cy5 image
Associates the CD3+ cells (parent objects) to the FoxP3+ cells (child objcets)
Checks the accuracy of detecting double positive cells by overlaying the outlines of the CD3+FoxP3+ cells on the grayscale FITC image
Measures intensities of CD3 expression and FoxP3 expression
Measures the correlation between CD3+ and FoxP3 intensities
Creates a color composite image with the three channels - DAPI, FITC, and Foxp3
Creates outlines of doublepositive cells on the merged (composite) image for visualization
Saves all the overlays to designated folders
Exports all measurements to a spreadsheet for downstream analysis
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