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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.
package io.github.mianalysis.mia.module.images.process.binary;
import org.scijava.Priority;
import org.scijava.plugin.Plugin;
import ij.ImagePlus;
import ij.ImageStack;
import ij.plugin.SubHyperstackMaker;
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.process.ImageMath;
import io.github.mianalysis.mia.module.images.process.InvertIntensity;
import io.github.mianalysis.mia.module.images.transform.registration.abstrakt.AbstractRegistration;
import io.github.mianalysis.mia.object.Workspace;
import io.github.mianalysis.mia.object.image.Image;
import io.github.mianalysis.mia.object.image.ImageFactory;
import io.github.mianalysis.mia.object.image.ImagePlusImage;
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.OutputImageP;
import io.github.mianalysis.mia.object.parameters.Parameters;
import io.github.mianalysis.mia.object.parameters.SeparatorP;
import io.github.mianalysis.mia.object.parameters.choiceinterfaces.BinaryLogicInterface;
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 sc.fiji.skeletonize3D.Skeletonize3D_;
/**
* Creates an skeletonised representation of a specific binary image in the workspace. The input and output images will be 8-bit with binary logic determined by the "Binary logic" parameter. Each minima will show the lowest local intensity region within a specific dynamic range. Local variation greater than this dynamic will result in the creation of more minima. Uses the plugin "MorphoLibJ".
*/
@Plugin(type = Module.class, priority=Priority.LOW, visible=true)
public class Skeletonise extends Module {
/**
*
*/
public static final String INPUT_SEPARATOR = "Image input/output";
/**
* Image from workspace to apply 3D skeletonisation operation to. This image will be 8-bit with binary logic determined by the "Binary logic" parameter.
*/
public static final String INPUT_IMAGE = "Input image";
/**
* When selected, the post-operation image will overwrite the input image in the workspace. Otherwise, the image will be saved to the workspace with the name specified by the "Output image" parameter.
*/
public static final String APPLY_TO_INPUT = "Apply to input image";
/**
* If "Apply to input image" is not selected, the post-operation image will be saved to the workspace with this name.
*/
public static final String OUTPUT_IMAGE = "Output image";
/**
*
*/
public static final String SKELETONISE_SEPARATOR = "Skeletonise controls";
/**
* Controls whether objects are considered to be white (255 intensity) on a black (0 intensity) background, or black on a white background.
*/
public static final String BINARY_LOGIC = "Binary logic";
public interface BinaryLogic extends BinaryLogicInterface {
}
public Skeletonise(Modules modules) {
super("Skeletonise", modules);
}
public static void process(Image image, boolean blackBackground) {
if (!blackBackground)
InvertIntensity.process(image);
// Iterating over all channels and timepoints
ImagePlus ipl = image.getImagePlus();
int nChannels = ipl.getNChannels();
int nSlices = ipl.getNSlices();
int nFrames = ipl.getNFrames();
Skeletonize3D_ skeletonize3d = new Skeletonize3D_();
for (int c = 1; c <= nChannels; c++) {
for (int t = 1; t <= nFrames; t++) {
ImagePlus iplOrig = SubHyperstackMaker.makeSubhyperstack(ipl, c + "-" + c, "1-" + nSlices, t + "-" + t);
// Running skeletonisation
skeletonize3d.setup("arg", iplOrig);
skeletonize3d.run(iplOrig.getProcessor());
ImagePlusImage.getSetStack(ipl, t, c, iplOrig.getStack());
}
}
// Multiplying back to the range 0-255
ImageMath.process(ipl, ImageMath.CalculationModes.MULTIPLY, 255);
// Inverting back to original logic
if (!blackBackground)
InvertIntensity.process(image);
}
@Override
public Category getCategory() {
return Categories.IMAGES_PROCESS_BINARY;
}
@Override
public String getVersionNumber() {
return "1.0.0";
}
@Override
public String getDescription() {
return "Creates an skeletonised representation of a specific binary image in the workspace. The input and output images will be 8-bit with binary logic determined by the \"" + BINARY_LOGIC + "\" parameter. Each minima will show the lowest local intensity region within a specific dynamic range. Local variation greater than this dynamic will result in the creation of more minima. Uses the plugin \"MorphoLibJ\".";
}
@Override
public Status process(Workspace workspace) {
// Getting input image
String inputImageName = parameters.getValue(INPUT_IMAGE,workspace);
Image inputImage = workspace.getImages().get(inputImageName);
ImagePlus inputImagePlus = inputImage.getImagePlus();
// Getting parameters
boolean applyToInput = parameters.getValue(APPLY_TO_INPUT,workspace);
String outputImageName = parameters.getValue(OUTPUT_IMAGE,workspace);
String binaryLogic = parameters.getValue(BINARY_LOGIC,workspace);
boolean blackBackground = binaryLogic.equals(BinaryLogic.BLACK_BACKGROUND);
// If applying to a new image, the input image is duplicated
if (!applyToInput)
inputImage = ImageFactory.createImage(outputImageName, inputImagePlus.duplicate());
process(inputImage,blackBackground);
// If the image is being saved as a new image, adding it to the workspace
if (!applyToInput) {
writeStatus("Adding image (" + outputImageName + ") to workspace");
workspace.addImage(inputImage);
}
if (showOutput)
inputImage.show();
return Status.PASS;
}
@Override
protected void initialiseParameters() {
parameters.add(new SeparatorP(INPUT_SEPARATOR, this));
parameters.add(new InputImageP(INPUT_IMAGE, this));
parameters.add(new BooleanP(APPLY_TO_INPUT, this, true));
parameters.add(new OutputImageP(OUTPUT_IMAGE, this));
parameters.add(new SeparatorP(SKELETONISE_SEPARATOR, this));
parameters.add(new ChoiceP(BINARY_LOGIC, this, BinaryLogic.BLACK_BACKGROUND, BinaryLogic.ALL));
addParameterDescriptions();
}
@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(APPLY_TO_INPUT));
if (!(boolean) parameters.getValue(APPLY_TO_INPUT,workspace))
returnedParameters.add(parameters.getParameter(OUTPUT_IMAGE));
returnedParameters.add(parameters.getParameter(SKELETONISE_SEPARATOR));
returnedParameters.add(parameters.getParameter(BINARY_LOGIC));
return returnedParameters;
}
@Override
public ImageMeasurementRefs updateAndGetImageMeasurementRefs() {
return null;
}
@Override
public ObjMeasurementRefs updateAndGetObjectMeasurementRefs() {
return null;
}
@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;
}
void addParameterDescriptions() {
parameters.get(INPUT_IMAGE).setDescription(
"Image from workspace to apply 3D skeletonisation operation to. This image will be 8-bit with binary logic determined by the \"" + BINARY_LOGIC + "\" parameter.");
parameters.get(APPLY_TO_INPUT).setDescription(
"When selected, the post-operation image will overwrite the input image in the workspace. Otherwise, the image will be saved to the workspace with the name specified by the \"" + OUTPUT_IMAGE + "\" parameter.");
parameters.get(OUTPUT_IMAGE).setDescription("If \"" + APPLY_TO_INPUT
+ "\" is not selected, the post-operation image will be saved to the workspace with this name.");
parameters.get(BINARY_LOGIC).setDescription(BinaryLogicInterface.getDescription());
}
}