io.github.mianalysis.mia.module.objects.measure.intensity.MeasureObjectGreyscaleKFunction Maven / Gradle / Ivy
// TODO: Could addRef an optional parameter to select the channel of the input image to use for measurement
package io.github.mianalysis.mia.module.objects.measure.intensity;
import org.apache.poi.ss.usermodel.Cell;
import org.apache.poi.ss.usermodel.Row;
import org.apache.poi.xssf.streaming.SXSSFSheet;
import org.apache.poi.xssf.streaming.SXSSFWorkbook;
import org.scijava.Priority;
import org.scijava.plugin.Plugin;
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.measure.MeasureGreyscaleKFunction;
import io.github.mianalysis.mia.module.images.transform.CropImage;
import io.github.mianalysis.mia.module.images.transform.ExtractSubstack;
import io.github.mianalysis.mia.module.inputoutput.abstrakt.AbstractSaver;
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.image.Image;
import io.github.mianalysis.mia.object.parameters.InputImageP;
import io.github.mianalysis.mia.object.parameters.InputObjectsP;
import io.github.mianalysis.mia.object.parameters.Parameters;
import io.github.mianalysis.mia.object.parameters.SeparatorP;
import io.github.mianalysis.mia.object.parameters.text.IntegerP;
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;
/**
* Created by sc13967 on 08/07/2022.
*/
/**
* Measure's Ripley's K-function for greyscale images on an object-by-object basis. This method is re-written from the publication "Extending Ripley’s K-Function to Quantify Aggregation in 2-D Grayscale Images" by M. Amgad, et al. (doi: 10.1371/journal.pone.0144404). Results are output to an Excel spreadsheet, with one file per input image.
*/
@Plugin(type = Module.class, priority = Priority.LOW, visible = true)
public class MeasureObjectGreyscaleKFunction extends AbstractSaver {
/**
*
*/
public static final String INPUT_SEPARATOR = "Object and image input";
/**
*
*/
public static final String INPUT_OBJECTS = "Input objects";
/**
*
*/
public static final String INPUT_IMAGE = "Input image";
/**
*
*/
public static final String FUNCTION_SEPARATOR = "K-function controls";
public static final String MINIMUM_RADIUS_PX = "Minimum radius (px)";
public static final String MAXIMUM_RADIUS_PX = "Maximum radius (px)";
public static final String RADIUS_INCREMENT = "Radius increment (px)";
public MeasureObjectGreyscaleKFunction(Modules modules) {
super("Measure object greyscale K-function", modules);
}
SXSSFWorkbook initialiseWorkbook() {
SXSSFWorkbook workbook = new SXSSFWorkbook();
SXSSFSheet sheet = workbook.createSheet();
int rowI = 0;
int colI = 0;
Row row = sheet.createRow(rowI++);
Cell cell = row.createCell(colI++);
cell.setCellValue("Timepoint");
cell = row.createCell(colI++);
cell.setCellValue("Slice");
cell = row.createCell(colI++);
cell.setCellValue("Radius (px)");
cell = row.createCell(colI++);
cell.setCellValue("Object ID");
cell = row.createCell(colI++);
cell.setCellValue("K-corr");
cell = row.createCell(colI++);
cell.setCellValue("Q01");
cell = row.createCell(colI++);
cell.setCellValue("Q99");
return workbook;
}
@Override
public Category getCategory() {
return Categories.OBJECTS_MEASURE_INTENSITY;
}
@Override
public String getVersionNumber() {
return "1.0.0";
}
@Override
public String getDescription() {
return "Measure's Ripley's K-function for greyscale images on an object-by-object basis. This method is re-written from the publication \"Extending Ripley’s K-Function to Quantify Aggregation in 2-D Grayscale Images\" by M. Amgad, et al. (doi: 10.1371/journal.pone.0144404). Results are output to an Excel spreadsheet, with one file per input image.";
}
@Override
public Status process(Workspace workspace) {
// Getting input objects
String inputImageName = parameters.getValue(INPUT_IMAGE, workspace);
String objectName = parameters.getValue(INPUT_OBJECTS, workspace);
Objs objects = workspace.getObjects().get(objectName);
int minRadius = parameters.getValue(MINIMUM_RADIUS_PX, workspace);
int maxRadius = parameters.getValue(MAXIMUM_RADIUS_PX, workspace);
int radiusInc = parameters.getValue(RADIUS_INCREMENT, workspace);
String appendSeriesMode = parameters.getValue(APPEND_SERIES_MODE, workspace);
String appendDateTimeMode = parameters.getValue(APPEND_DATETIME_MODE, workspace);
String suffix = parameters.getValue(SAVE_SUFFIX, workspace);
SXSSFWorkbook workbook = initialiseWorkbook();
SXSSFSheet sheet = workbook.getSheetAt(0);
Image inputImage = workspace.getImage(inputImageName);
int rowI = 1;
int count = 0;
int total = objects.size();
for (Obj object : objects.values()) {
int t = object.getT();
// Getting images cropped to this object
double[][] extents = object.getExtents(true, false);
int top = (int) Math.round(extents[1][0]);
int left = (int) Math.round(extents[0][0]);
int width = (int) Math.round(extents[0][1] - left) + 1;
int height = (int) Math.round(extents[1][1] - top) + 1;
Image cropImage = CropImage.cropImage(inputImage, "Crop", left, top, width, height);
// Cropping image in Z
int minZ = (int) Math.round(extents[2][0]);
int maxZ = (int) Math.round(extents[2][1]);
Image subsImage = ExtractSubstack.extractSubstack(cropImage, "Substack", "1", (minZ + 1) + "-" + (maxZ + 1),
"1");
// Getting
Image maskImage = object.getAsTightImage("Mask");
for (int z = 0; z < maskImage.getImagePlus().getNSlices(); z++) {
Image currImage = ExtractSubstack.extractSubstack(subsImage, "TimepointImage", "1",
String.valueOf(z + 1), String.valueOf(t + 1));
Image currMask = ExtractSubstack.extractSubstack(maskImage, "TimepointMask", "1",
String.valueOf(z + 1), String.valueOf(t + 1));
for (int r = minRadius; r <= maxRadius; r = r + radiusInc) {
double[] kRes = MeasureGreyscaleKFunction.calculateGSKfunction(currImage, r, currMask);
int colI = 0;
Row row = sheet.createRow(rowI++);
Cell cell = row.createCell(colI++);
cell.setCellValue(t);
cell = row.createCell(colI++);
cell.setCellValue(z);
cell = row.createCell(colI++);
cell.setCellValue(r);
cell = row.createCell(colI++);
cell.setCellValue(object.getID());
cell = row.createCell(colI++);
cell.setCellValue(kRes[0]);
cell = row.createCell(colI++);
cell.setCellValue(kRes[1]);
cell = row.createCell(colI++);
cell.setCellValue(kRes[2]);
writeProgressStatus(++count, total, "steps");
}
}
writeProgressStatus(++count, total, "objects");
}
String outputPath = getOutputPath(modules, workspace);
String outputName = getOutputName(modules, workspace);
// Adding last bits to name
outputPath = outputPath + outputName;
outputPath = appendSeries(outputPath, workspace, appendSeriesMode);
outputPath = appendDateTime(outputPath, appendDateTimeMode);
outputPath = outputPath + suffix + ".xlsx";
MeasureIntensityAlongPath.writeDistancesFile(workbook, outputPath);
return Status.PASS;
}
@Override
protected void initialiseParameters() {
super.initialiseParameters();
parameters.add(new SeparatorP(INPUT_SEPARATOR, this));
parameters.add(new InputObjectsP(INPUT_OBJECTS, this));
parameters.add(new InputImageP(INPUT_IMAGE, this));
parameters.add(new SeparatorP(FUNCTION_SEPARATOR, this));
parameters.add(new IntegerP(MINIMUM_RADIUS_PX, this, 3));
parameters.add(new IntegerP(MAXIMUM_RADIUS_PX, this, 15));
parameters.add(new IntegerP(RADIUS_INCREMENT, this, 1));
addParameterDescriptions();
}
@Override
public Parameters updateAndGetParameters() {
Workspace workspace = null;
Parameters returnedParameters = new Parameters();
returnedParameters.add(parameters.getParameter(INPUT_SEPARATOR));
returnedParameters.add(parameters.getParameter(INPUT_OBJECTS));
returnedParameters.add(parameters.getParameter(INPUT_IMAGE));
returnedParameters.add(parameters.getParameter(FUNCTION_SEPARATOR));
returnedParameters.add(parameters.getParameter(MINIMUM_RADIUS_PX));
returnedParameters.add(parameters.getParameter(MAXIMUM_RADIUS_PX));
returnedParameters.add(parameters.getParameter(RADIUS_INCREMENT));
returnedParameters.addAll(super.updateAndGetParameters());
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;
}
protected void addParameterDescriptions() {
}
}
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