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1.0_GridQuant_calibrate.groovy
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1.0_GridQuant_calibrate.groovy
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// 1.0_GridQuant_calibrate.groovy
// This is step 1.0 of GridQuant pipeline. It consists in calibrating the parameters for automated cell detection on a small representative region of interest (ROI), in order to allow visual inspection before performing cell detection on the entire image.
// --- Usage ---
// 1) Load the image in QuPath.
// 2) Draw a small representative ROI
// 3) Uncomment the line below corresponding to the channel of interest. You might need to change the channel name.
// 4) Tune the parameters for cell detection
// 5) Run the script
// 6) Check visually that the automated cell detection is reasonable. You might find it useful to switch to grayscale.
// 7) Repeat steps 4-6 until you are satisfied
// 8) Repeat steps 3-7 for all channels
// 9) Repeat steps 2-8 on a few more representative ROIs for validation
// 10) Copy the script lines with your final parameters and paste them in the right position in the next script of GridQuant, i.e. '1.1_GridQuant_getAllDetections.groovy'
// --- Input ---
// Rectangular ROIs drawn by the user on the image
// --- Output ---
// Cells detected for a given channel
// --- Other parameters ---
// Cell detection parameters
// --- Requires ---
// QuPath (tested on: v0.2.0-m4, on a Unix system)
// Author: Daniele Tavernari
// Please cite: Tavernari et al., 2021 (see full citation on GitHub repository's README)
println "Script starting..."
import qupath.lib.objects.PathAnnotationObject
import qupath.lib.objects.classes.PathClassFactory
import qupath.lib.roi.RectangleROI
import qupath.lib.gui.scripting.QPEx
// Input
//
clearDetections();
selectAnnotations();
def imageData = QPEx.getCurrentImageData()
// Uncomment the appropriate line
// macrophages
// runPlugin('qupath.imagej.detect.cells.WatershedCellDetection', '{"detectionImage": "Alexa 594", "requestedPixelSizeMicrons": 0.5, "backgroundRadiusMicrons": 8.0, "medianRadiusMicrons": 0.0, "sigmaMicrons": 1.5, "minAreaMicrons": 10.0, "maxAreaMicrons": 400.0, "threshold": 600.0, "watershedPostProcess": false, "cellExpansionMicrons": 0.0, "includeNuclei": true, "smoothBoundaries": true, "makeMeasurements": true}');
// CD8
// runPlugin('qupath.imagej.detect.cells.WatershedCellDetection', '{"detectionImage": "RFP", "requestedPixelSizeMicrons": 0.5, "backgroundRadiusMicrons": 8.0, "medianRadiusMicrons": 0.0, "sigmaMicrons": 1.5, "minAreaMicrons": 5.0, "maxAreaMicrons": 400.0, "threshold": 400.0, "watershedPostProcess": false, "cellExpansionMicrons": 0.0, "includeNuclei": true, "smoothBoundaries": true, "makeMeasurements": true}');
// CD4
// runPlugin('qupath.imagej.detect.cells.WatershedCellDetection', '{"detectionImage": "CFP", "requestedPixelSizeMicrons": 0.5, "backgroundRadiusMicrons": 8.0, "medianRadiusMicrons": 0.0, "sigmaMicrons": 1.5, "minAreaMicrons": 10.0, "maxAreaMicrons": 400.0, "threshold": 600.0, "watershedPostProcess": false, "cellExpansionMicrons": 0.0, "includeNuclei": true, "smoothBoundaries": true, "makeMeasurements": true}');
// Bcell
// runPlugin('qupath.imagej.detect.cells.WatershedCellDetection', '{"detectionImage": "FITC", "requestedPixelSizeMicrons": 0.5, "backgroundRadiusMicrons": 8.0, "medianRadiusMicrons": 0.0, "sigmaMicrons": 1.5, "minAreaMicrons": 10.0, "maxAreaMicrons": 400.0, "threshold": 300.0, "watershedPostProcess": true, "cellExpansionMicrons": 0.0, "includeNuclei": true, "smoothBoundaries": true, "makeMeasurements": true}');
// Ki67
// runPlugin('qupath.imagej.detect.cells.WatershedCellDetection', '{"detectionImage": "CY5", "requestedPixelSizeMicrons": 0.5, "backgroundRadiusMicrons": 8.0, "medianRadiusMicrons": 0.0, "sigmaMicrons": 1.5, "minAreaMicrons": 5.0, "maxAreaMicrons": 400.0, "threshold": 200.0, "watershedPostProcess": false, "cellExpansionMicrons": 0.0, "includeNuclei": true, "smoothBoundaries": true, "makeMeasurements": true}');
println "Done"