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ModularImageAnalysis (MIA) is an ImageJ plugin which provides a modular framework for assembling image and object analysis workflows. Detected objects can be transformed, filtered, measured and related. Analysis workflows are batch-enabled by default, allowing easy processing of high-content datasets.

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// TODO: See how TrackMate behaves with different channels.  Currently always assigns channel to "0".

package io.github.mianalysis.mia.module.objects.detect;

import java.awt.Color;
import java.util.ArrayList;
import java.util.HashMap;

import org.scijava.Priority;
import org.scijava.plugin.Plugin;

import fiji.plugin.trackmate.Logger;
import fiji.plugin.trackmate.Model;
import fiji.plugin.trackmate.Settings;
import fiji.plugin.trackmate.Spot;
import fiji.plugin.trackmate.SpotCollection;
import fiji.plugin.trackmate.TrackMate;
import fiji.plugin.trackmate.detection.DetectorKeys;
import fiji.plugin.trackmate.detection.LogDetectorFactory;
import ij.ImagePlus;
import ij.measure.Calibration;
import ij.plugin.Duplicator;
import io.github.mianalysis.mia.MIA;
import io.github.mianalysis.mia.module.Categories;
import io.github.mianalysis.mia.module.Category;
import io.github.mianalysis.mia.module.Module;
import io.github.mianalysis.mia.module.Modules;
import io.github.mianalysis.mia.module.images.transform.ExtractSubstack;
import io.github.mianalysis.mia.module.objects.process.GetLocalObjectRegion;
import io.github.mianalysis.mia.module.visualise.overlays.AddObjectCentroid;
import io.github.mianalysis.mia.module.visualise.overlays.AddObjectOutline;
import io.github.mianalysis.mia.object.Measurement;
import io.github.mianalysis.mia.object.Obj;
import io.github.mianalysis.mia.object.Objs;
import io.github.mianalysis.mia.object.Workspace;
import io.github.mianalysis.mia.object.coordinates.Point;
import io.github.mianalysis.mia.object.coordinates.volume.PointOutOfRangeException;
import io.github.mianalysis.mia.object.coordinates.volume.SpatCal;
import io.github.mianalysis.mia.object.coordinates.volume.VolumeType;
import io.github.mianalysis.mia.object.image.Image;
import io.github.mianalysis.mia.object.parameters.BooleanP;
import io.github.mianalysis.mia.object.parameters.ChoiceP;
import io.github.mianalysis.mia.object.parameters.InputImageP;
import io.github.mianalysis.mia.object.parameters.Parameters;
import io.github.mianalysis.mia.object.parameters.SeparatorP;
import io.github.mianalysis.mia.object.parameters.objects.OutputObjectsP;
import io.github.mianalysis.mia.object.parameters.text.DoubleP;
import io.github.mianalysis.mia.object.refs.ObjMeasurementRef;
import io.github.mianalysis.mia.object.refs.collections.ImageMeasurementRefs;
import io.github.mianalysis.mia.object.refs.collections.MetadataRefs;
import io.github.mianalysis.mia.object.refs.collections.ObjMeasurementRefs;
import io.github.mianalysis.mia.object.refs.collections.ObjMetadataRefs;
import io.github.mianalysis.mia.object.refs.collections.ParentChildRefs;
import io.github.mianalysis.mia.object.refs.collections.PartnerRefs;
import io.github.mianalysis.mia.object.system.Status;
import io.github.mianalysis.mia.object.units.SpatialUnit;
import io.github.mianalysis.mia.object.units.TemporalUnit;
import io.github.mianalysis.mia.process.ColourFactory;
import io.github.mianalysis.mia.process.exceptions.IntegerOverflowException;
import io.github.mianalysis.mia.process.imagej.IntensityMinMax;

/**
 * Created by sc13967 on 15/05/2017.
 */

/**
* Detects spot-like features in 2D and 3D using TrackMate's LogDetector.  By default, detected spots are stored as individual, single pixel, objects centred on the detected feature.  Optionally, spots can be given area or volume based on the estimated size of the spot.  Adds measurements to each output spot for estimated radius and quality.  If sub-pixel localisation is specified, the sub-pixel centroid location in X,Y and Z is also stored as a measurement.

For more information, see the TrackMate documentation. */ @Plugin(type = Module.class, priority = Priority.LOW, visible = true) public class SpotDetection extends Module { /** * */ public static final String INPUT_SEPARATOR = "Image input, object output"; /** * Image in which to detect spots. */ public static final String INPUT_IMAGE = "Input image"; /** * Spot objects that will be added to the workspace. */ public static final String OUTPUT_SPOT_OBJECTS = "Output spot objects"; /** * */ public static final String SPOT_SEPARATOR = "Spot detection"; /** * */ public static final String DETECTION_MODE = "Detection mode"; /** * Enable if spatial parameters (e.g. "Radius") are being specified in calibrated units. If disabled, parameters are assumed to be specified in pixel units. */ public static final String CALIBRATED_UNITS = "Calibrated units"; /** * Enable TrackMate's "Subpixel localisation" functionality. When enabled, subpixel centroid coordinates will be stored as measurements associated with each detected object. */ public static final String DO_SUBPIXEL_LOCALIZATION = "Do sub-pixel localisation"; /** * Enable TrackMate's "Median filtering" functionality. */ public static final String DO_MEDIAN_FILTERING = "Median filtering"; /** * Expected radius of spots in the input image. Specified in pixel units, unless "Calibrated units" is selected. */ public static final String RADIUS = "Radius"; /** * Threshold for spot detection. Threshold is applied to filtered image (Laplacian of Gaussian), so will be affected by the specified "Radius" value. Increase this value to make detection more selective (i.e. detect fewer spots). */ public static final String THRESHOLD = "Threshold"; /** * When enabled, output spot objects will have explicit size (rather than a single, centroid coordinate) determined by the TrackMate-calculated estimated diameter. */ public static final String ESTIMATE_SIZE = "Estimate spot size"; public interface DetectionModes { String SLICE_BY_SLICE = "2D (slice-by-slice)"; String THREE_D = "3D"; String[] ALL = new String[] { SLICE_BY_SLICE, THREE_D }; } public interface Measurements { String RADIUS_PX = "SPOT_DETECT // RADIUS_(PX)"; String RADIUS_CAL = "SPOT_DETECT // RADIUS_(${SCAL})"; String QUALITY = "SPOT_DETECT // QUALITY"; String X_CENTROID_PX = "SPOT_DETECT // X_CENTROID_(PX)"; String X_CENTROID_CAL = "SPOT_DETECT // X_CENTROID_(${SCAL})"; String Y_CENTROID_PX = "SPOT_DETECT // Y_CENTROID_(PX)"; String Y_CENTROID_CAL = "SPOT_DETECT // Y_CENTROID_(${SCAL})"; String Z_CENTROID_SLICE = "SPOT_DETECT // Z_CENTROID_(SLICE)"; String Z_CENTROID_CAL = "SPOT_DETECT // Z_CENTROID_(${SCAL})"; } public SpotDetection(Modules modules) { super("Spot detection", modules); } public ArrayList processStack(Image inputImage, Objs spotObjects, boolean estimateSize, Workspace workspace) { ImagePlus ipl = inputImage.getImagePlus(); SpatCal calibration = SpatCal.getFromImage(ipl); Calibration cal = ipl.getCalibration(); ipl.setCalibration(null); // Initialising TrackMate model to store data Model model = new Model(); model.setLogger(Logger.VOID_LOGGER); Settings settings = initialiseSettings(ipl, calibration, workspace); TrackMate trackmate = new TrackMate(model, settings); if (!trackmate.execDetection()) MIA.log.writeError(trackmate.getErrorMessage()); if (!trackmate.computeSpotFeatures(false)) MIA.log.writeError(trackmate.getErrorMessage()); ArrayList newSpots = addSpots(model, spotObjects); if (estimateSize) estimateSpotSize(spotObjects, ipl); // Reapplying calibration to input image inputImage.getImagePlus().setCalibration(cal); return newSpots; } public Objs processSlice(Image inputImage, Objs spotObjects, boolean estimateSize, Workspace workspace) { int nSlices = inputImage.getImagePlus().getNSlices(); for (int z=0;z newSpots = processStack(sliceImage, spotObjects, estimateSize, workspace); // Putting the new spots at the correct Z-plane for (Obj newSpot:newSpots) newSpot.translateCoords(0, 0, z); } return spotObjects; } public Settings initialiseSettings(ImagePlus ipl, SpatCal calibration, Workspace workspace) { boolean calibratedUnits = parameters.getValue(CALIBRATED_UNITS,workspace); boolean subpixelLocalisation = parameters.getValue(DO_SUBPIXEL_LOCALIZATION,workspace); boolean medianFiltering = parameters.getValue(DO_MEDIAN_FILTERING,workspace); double radius = parameters.getValue(RADIUS,workspace); double threshold = parameters.getValue(THRESHOLD,workspace); // Applying conversion to parameters if (calibratedUnits) radius = radius / calibration.getDppXY(); // Initialising settings for TrackMate Settings settings = new Settings(ipl); settings.detectorFactory = new LogDetectorFactory(); settings.detectorSettings.put(DetectorKeys.KEY_DO_SUBPIXEL_LOCALIZATION, subpixelLocalisation); settings.detectorSettings.put(DetectorKeys.KEY_DO_MEDIAN_FILTERING, medianFiltering); settings.detectorSettings.put(DetectorKeys.KEY_RADIUS, radius); settings.detectorSettings.put(DetectorKeys.KEY_THRESHOLD, threshold); settings.detectorSettings.put(DetectorKeys.KEY_TARGET_CHANNEL, 1); return settings; } public ArrayList addSpots(Model model, Objs spotObjects) throws IntegerOverflowException { ArrayList newSpots = new ArrayList<>(); boolean doSubpixel = parameters.getValue(DO_SUBPIXEL_LOCALIZATION,null); SpotCollection spots = model.getSpots(); for (Spot spot : spots.iterable(false)) { Obj spotObject = spotObjects.createAndAddNewObject(VolumeType.POINTLIST, spot.ID()); try { spotObject.add((int) spot.getDoublePosition(0), (int) spot.getDoublePosition(1), (int) spot.getDoublePosition(2)); } catch (PointOutOfRangeException e) { MIA.log.writeError(e); } spotObject.setT((int) Math.round(spot.getFeature(Spot.FRAME))); addSpotMeasurements(spotObject, spot, doSubpixel); newSpots.add(spotObject); } return newSpots; } void addSpotMeasurements(Obj spotObject, Spot spot, boolean doSubpixel) { double dppXY = spotObject.getDppXY(); double dppZ = spotObject.getDppZ(); spotObject.addMeasurement(new Measurement(Measurements.RADIUS_PX, spot.getFeature(Spot.RADIUS))); spotObject.addMeasurement(new Measurement(Measurements.RADIUS_CAL, spot.getFeature(Spot.RADIUS) * dppXY)); spotObject.addMeasurement(new Measurement(Measurements.QUALITY, spot.getFeature(Spot.QUALITY))); if (doSubpixel) { spotObject.addMeasurement(new Measurement(Measurements.X_CENTROID_PX, spot.getFeature(Spot.POSITION_X))); spotObject.addMeasurement( new Measurement(Measurements.X_CENTROID_CAL, spot.getFeature(Spot.POSITION_X) * dppXY)); spotObject.addMeasurement(new Measurement(Measurements.Y_CENTROID_PX, spot.getFeature(Spot.POSITION_Y))); spotObject.addMeasurement( new Measurement(Measurements.Y_CENTROID_CAL, spot.getFeature(Spot.POSITION_Y) * dppXY)); spotObject.addMeasurement(new Measurement(Measurements.Z_CENTROID_SLICE, spot.getFeature(Spot.POSITION_Z))); spotObject.addMeasurement( new Measurement(Measurements.Z_CENTROID_CAL, spot.getFeature(Spot.POSITION_Z) * dppZ)); } } public void estimateSpotSize(Objs spotObjects, ImagePlus ipl) throws IntegerOverflowException { Objs tempObjects = new Objs("SpotVolume", spotObjects); // Replacing spot volumes with explicit volume for (Obj spotObject : spotObjects.values()) { int radius = (int) Math.round(spotObject.getMeasurement(Measurements.RADIUS_PX).getValue()); Point cent = spotObject.getMeanCentroid(true, false); int[] centroid = new int[] { (int) Math.round(cent.getX()), (int) Math.round(cent.getY()), (int) Math.round(cent.getZ()) }; Obj volumeObject = GetLocalObjectRegion.getLocalRegion(spotObject, tempObjects, centroid, radius, false); spotObject.getCoordinateSet().clear(); spotObject.getCoordinateSet().addAll(volumeObject.getCoordinateSet()); spotObject.clearSurface(); spotObject.clearCentroid(); spotObject.clearProjected(); spotObject.clearROIs(); } } public void showObjects(ImagePlus ipl, Objs spotObjects, boolean estimateSize) { HashMap hues = ColourFactory.getSingleColourValues(spotObjects, ColourFactory.SingleColours.ORANGE); HashMap colours = ColourFactory.getColours(hues, 100); String pointSize = AddObjectCentroid.PointSizes.SMALL; String pointType = AddObjectCentroid.PointTypes.CIRCLE; // Creating a duplicate of the input image ipl = new Duplicator().run(ipl); IntensityMinMax.run(ipl, true); // Adding the overlay if (estimateSize) AddObjectOutline.addOverlay(ipl, spotObjects, 1, 1, colours, false, true); else AddObjectCentroid.addOverlay(ipl, spotObjects, colours, pointSize, pointType, false, true); ipl.setPosition(1, 1, 1); ipl.updateChannelAndDraw(); // Displaying the overlay ipl.show(); } @Override public Category getCategory() { return Categories.OBJECTS_DETECT; } @Override public String getVersionNumber() { return "1.0.0"; } @Override public String getDescription() { return "Detects spot-like features in 2D and 3D using TrackMate's LogDetector. By default, detected spots are stored as individual, single pixel, objects centred on the detected feature. Optionally, spots can be given area or volume based on the estimated size of the spot. Adds measurements to each output spot for estimated radius and quality. If sub-pixel localisation is specified, the sub-pixel centroid location in X,Y and Z is also stored as a measurement." + "

For more information, see the TrackMate documentation."; } @Override public Status process(Workspace workspace) { // Getting parameters String inputImageName = parameters.getValue(INPUT_IMAGE,workspace); String spotObjectsName = parameters.getValue(OUTPUT_SPOT_OBJECTS,workspace); String detectionMode = parameters.getValue(DETECTION_MODE,workspace); boolean estimateSize = parameters.getValue(ESTIMATE_SIZE,workspace); // Loading input image Image inputImage = workspace.getImage(inputImageName); ImagePlus ipl = inputImage.getImagePlus(); SpatCal calibration = SpatCal.getFromImage(ipl); int nFrames = ipl.getNFrames(); double frameInterval = ipl.getCalibration().frameInterval; Objs spotObjects = new Objs(spotObjectsName, calibration, nFrames, frameInterval, TemporalUnit.getOMEUnit()); workspace.addObjects(spotObjects); switch (detectionMode) { case DetectionModes.SLICE_BY_SLICE: processSlice(inputImage, spotObjects, estimateSize, workspace); break; case DetectionModes.THREE_D: processStack(inputImage, spotObjects, estimateSize, workspace); break; } // Displaying objects (if selected) if (showOutput) showObjects(ipl, spotObjects, estimateSize); return Status.PASS; } @Override protected void initialiseParameters() { parameters.add(new SeparatorP(INPUT_SEPARATOR, this)); parameters.add(new InputImageP(INPUT_IMAGE, this, "", "Image in which to detect spots.")); parameters.add( new OutputObjectsP(OUTPUT_SPOT_OBJECTS, this, "", "Spot objects that will be added to the workspace.")); parameters.add(new SeparatorP(SPOT_SEPARATOR, this)); parameters.add(new ChoiceP(DETECTION_MODE, this, DetectionModes.THREE_D, DetectionModes.ALL)); parameters.add(new BooleanP(CALIBRATED_UNITS, this, false, "Enable if spatial parameters (e.g. \"" + RADIUS + "\") are being specified in calibrated units. If disabled, parameters are assumed to be specified in pixel units.")); parameters.add(new BooleanP(DO_SUBPIXEL_LOCALIZATION, this, true, "Enable TrackMate's \"Subpixel localisation\" functionality. When enabled, subpixel centroid coordinates will be stored as measurements associated with each detected object.")); parameters.add(new BooleanP(DO_MEDIAN_FILTERING, this, false, "Enable TrackMate's \"Median filtering\" functionality.")); parameters.add(new DoubleP(RADIUS, this, 2.0, "Expected radius of spots in the input image. Specified in pixel units, unless \"" + CALIBRATED_UNITS + "\" is selected.")); parameters.add(new DoubleP(THRESHOLD, this, 10.0, "Threshold for spot detection. Threshold is applied to filtered image (Laplacian of Gaussian), so will be affected by the specified \"" + RADIUS + "\" value. Increase this value to make detection more selective (i.e. detect fewer spots).")); parameters.add(new BooleanP(ESTIMATE_SIZE, this, false, "When enabled, output spot objects will have explicit size (rather than a single, centroid coordinate) determined by the TrackMate-calculated estimated diameter.")); } @Override public Parameters updateAndGetParameters() { Workspace workspace = null; Parameters returnedParameters = new Parameters(); returnedParameters.add(parameters.getParameter(INPUT_SEPARATOR)); returnedParameters.add(parameters.getParameter(INPUT_IMAGE)); returnedParameters.add(parameters.getParameter(OUTPUT_SPOT_OBJECTS)); returnedParameters.add(parameters.getParameter(SPOT_SEPARATOR)); returnedParameters.add(parameters.get(DETECTION_MODE)); returnedParameters.add(parameters.getParameter(CALIBRATED_UNITS)); returnedParameters.add(parameters.getParameter(DO_SUBPIXEL_LOCALIZATION)); returnedParameters.add(parameters.getParameter(DO_MEDIAN_FILTERING)); returnedParameters.add(parameters.getParameter(RADIUS)); returnedParameters.add(parameters.getParameter(THRESHOLD)); returnedParameters.add(parameters.getParameter(ESTIMATE_SIZE)); return returnedParameters; } @Override public ImageMeasurementRefs updateAndGetImageMeasurementRefs() { return null; } @Override public ObjMeasurementRefs updateAndGetObjectMeasurementRefs() { Workspace workspace = null; ObjMeasurementRefs returnedRefs = new ObjMeasurementRefs(); String outputSpotObjectsName = parameters.getValue(OUTPUT_SPOT_OBJECTS,workspace); ObjMeasurementRef reference = objectMeasurementRefs.getOrPut(Measurements.RADIUS_PX); reference.setObjectsName(outputSpotObjectsName); reference.setDescription("Radius used as size estimate for spot detection. Measured in pixel units."); returnedRefs.add(reference); reference = objectMeasurementRefs.getOrPut(Measurements.RADIUS_CAL); reference.setObjectsName(outputSpotObjectsName); reference.setDescription("Radius used as size estimate for spot detection. Measured in calibrated " + "(" + SpatialUnit.getOMEUnit().getSymbol() + ") units."); returnedRefs.add(reference); reference = objectMeasurementRefs.getOrPut(Measurements.QUALITY); reference.setObjectsName(outputSpotObjectsName); returnedRefs.add(reference); if ((boolean) parameters.getValue(DO_SUBPIXEL_LOCALIZATION,workspace)) { reference = objectMeasurementRefs.getOrPut(Measurements.X_CENTROID_PX); reference.setObjectsName(outputSpotObjectsName); returnedRefs.add(reference); reference = objectMeasurementRefs.getOrPut(Measurements.X_CENTROID_CAL); reference.setObjectsName(outputSpotObjectsName); returnedRefs.add(reference); reference = objectMeasurementRefs.getOrPut(Measurements.Y_CENTROID_PX); reference.setObjectsName(outputSpotObjectsName); returnedRefs.add(reference); reference = objectMeasurementRefs.getOrPut(Measurements.Y_CENTROID_CAL); reference.setObjectsName(outputSpotObjectsName); returnedRefs.add(reference); reference = objectMeasurementRefs.getOrPut(Measurements.Z_CENTROID_SLICE); reference.setObjectsName(outputSpotObjectsName); returnedRefs.add(reference); reference = objectMeasurementRefs.getOrPut(Measurements.Z_CENTROID_CAL); reference.setObjectsName(outputSpotObjectsName); returnedRefs.add(reference); } return returnedRefs; } @Override public ObjMetadataRefs updateAndGetObjectMetadataRefs() { return null; } @Override public MetadataRefs updateAndGetMetadataReferences() { return null; } @Override public ParentChildRefs updateAndGetParentChildRefs() { return null; } @Override public PartnerRefs updateAndGetPartnerRefs() { return null; } @Override public boolean verify() { return true; } }




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