[ImageJ-devel] Qeustion regarding labeling and regions of interest in imglib2

[Robert Haase]

Hi All,

I'm quite new in developing imagej-plugins using imglib2. I ran in some 
issues working with Labeling and Regions in imglib2. Hopefully, somebody 
of you can help me. This is what I would like to do:

I have an image(Plus) where pixel values correspond to the desired 
labeling. Thus, all pixels with value 1 belong to label 1, all pixels 
with value 2 belong to label 2 and so on. Labelled regions cannot 
overlap. Now, I would like to create an ImgLabeling from the given 
ImagePlus to manage the corresponding regions of interest in imglib2 and 
to do the analysis using this library.
I was able to create some functions which appear to do the 
transformation, however, the results are not fully understandable for 
me. On bottom of this email you find "minimal" example code (which runs 
fine in eclipse set up for ImageJ-development) which creates a 
labelmap-ImagePlus, transforms it into ImgLabeling and displays binary 
images corresponding to the regions. However, when I input a label with 
100 pixels, the corresponding output region may or may not have the same 
number of pixels. So the output of the program is:

Number of input pixels in label 0: 9400
Number of input pixels in label 1: 100
Number of input pixels in label 2: 200
Number of input pixels in label 3: 300
Number of input pixels in label 4: 0
Number of out pixels in region: 10000
Number of out pixels in region: 600
Number of out pixels in region: 500
Number of out pixels in region: 300

As you can see, the number of read-in pixels is not equal to the number 
of pixels which are positive afterwards in the corresponding region. The 
program visualises the images as well. The mistake in the result is 
obvious. My mistake in the code is not that obvious to me.

I guess, I interpret the meaning of regions and/or labels wrong. 
Hopefully somebody of you may point me in the right direction to do the 
above mentioned transformation properly.

Thanks a lot in advance!
Robert

LabelingExample.java ----------------------------


import ij.ImagePlus;
import ij.gui.NewImage;
import ij.process.ImageProcessor;

import java.awt.Rectangle;
import java.io.IOException;
import java.util.Set;

import net.imglib2.Cursor;
import net.imglib2.RandomAccess;
import net.imglib2.RandomAccessibleInterval;
import net.imglib2.img.Img;
import net.imglib2.img.array.ArrayImgs;
import net.imglib2.img.display.imagej.ImageJFunctions;
import net.imglib2.roi.labeling.ImgLabeling;
import net.imglib2.roi.labeling.LabelRegion;
import net.imglib2.roi.labeling.LabelRegionCursor;
import net.imglib2.roi.labeling.LabelRegions;
import net.imglib2.roi.labeling.LabelingType;
import net.imglib2.type.logic.BitType;
import net.imglib2.type.logic.BoolType;
import net.imglib2.type.numeric.integer.IntType;
import net.imglib2.type.numeric.real.FloatType;

public class LabelingExample {
     LabelingExample()
     {
         new ij.ImageJ();

         //Create and show a simple test image, 100x100
         ImagePlus imp = createTestImage();
         imp.show();

         //Create an ImgLabeling from the ImagePlus
         ImgLabeling<Integer, IntType> labeling = 
getIntIntImgLabellingFromLabelMapImagePlus(imp);

         //Read out regions and labelNames
         LabelRegions<Integer> regions = new 
LabelRegions<Integer>(labeling);
         Set<Integer> labelNames = labeling.getMapping().getLabels();

         //Visualise the labels as binary images.
         for (Integer labelName : labelNames )
         {
             LabelRegion<Integer> lr = regions.getLabelRegion(labelName);
             ImageJFunctions.show(labelRegionToBinaryImage(lr, 
(Img<IntType>)labeling.getIndexImg()));
         }
     }

     //Create an image with three labels (+background)
     //The three labels have an area of 100, 200 and 300.
     private ImagePlus createTestImage()
     {
         ImagePlus imp = NewImage.createByteImage("Test iamge", 100, 
100, 1, NewImage.FILL_BLACK);
         ImageProcessor ip = imp.getProcessor();
         ip.setRoi(new Rectangle(10, 10, 10, 10));
         ip.setColor(1);
         ip.fill();
         ip.setRoi(new Rectangle(20, 20, 10, 20));
         ip.setColor(2);
         ip.fill();
         ip.setRoi(new Rectangle(40, 40, 10, 30));
         ip.setColor(3);
         ip.fill();

         return imp;
     }

     //Transform an ImagePlus to a Labeling Imp. The original pixel 
value should be the label afterwards.
     public static ImgLabeling<Integer, IntType> 
getIntIntImgLabellingFromLabelMapImagePlus(ImagePlus labelMap)
     {
         final RandomAccessibleInterval< IntType > img = 
ImageJFunctions.wrapNumeric(labelMap);
         Img< FloatType > img2 = ImageJFunctions.convertFloat(labelMap);
         final long[] dims = new long[ img.numDimensions() ];

         ImgLabeling< Integer, IntType > labeling = new ImgLabeling< 
Integer, IntType >( img );

         Cursor<LabelingType<Integer>> labelCursor = labeling.cursor();
         RandomAccess<FloatType> imageRA = img2.randomAccess();

         // Go through the whole image again and again for every single 
label, until no more label is found.
         // If you know a more efficient way to do this, tell me...
         int currentLabel = 0;
         boolean anythingFound = true;
         while (anythingFound)
         {
             anythingFound = false;
             labelCursor.reset();

             //Go through the whole image and add every pixel, that 
belongs to the currently processed label
             int count = 0;
             while (labelCursor.hasNext())
             {
                 LabelingType<Integer> element = labelCursor.next();
                 imageRA.setPosition(labelCursor);

                 int i = (int)(imageRA.get().get());
                 if (i == currentLabel)
                 {
                     element.add(i);
                     anythingFound = true;
                     count ++;
                 }
             }
             System.out.println("Number of input pixels in label " + 
currentLabel + ": " + count);
             currentLabel++;
         }
         ImageJFunctions.show(labeling.getIndexImg());
         return labeling;
     }

     //Transform a Region to a binary image, which can be displayed
     public static < T, F > Img<BitType> 
labelRegionToBinaryImage(LabelRegion<T> region, Img<F> img)
     {
         final long[] pos = new long[ img.numDimensions() ];
         final long[] dims = new long[ img.numDimensions() ];
         img.dimensions( dims );

         final Img< BitType > newImage = ArrayImgs.bits( dims );

         RandomAccess<BitType> imageRA = newImage.randomAccess();
         LabelRegionCursor regionCursor = region.cursor();

         int count = 0;
         while (regionCursor.hasNext())
         {
             //Read yes/no from region
             BoolType regionElement = regionCursor.next();
             regionCursor.localize(pos);
             imageRA.setPosition(pos);
             BitType imageElement = imageRA.get();

             //Draw binary image pixel by pixel
             if (regionElement.get())
             {
                 count++;
                 imageElement.set(true);
             }
             else
             {
                 imageElement.set(false);
             }
         }
         System.out.println("Number of output pixels in region: " + count);
         return newImage;
     }



     //Just to run it
     public static void main(final String... args) throws IOException
     {
         new LabelingExample();
     }
}




-- 
Robert Haase
Bio-Image informatics, Scientific Computing Facility

Max Planck Institute CBG
Pfotenhauer Str. 108, 01307 Dresden
room: 106 (s)
phone: +49 351 210 2972
fax:   +49 351 210 1689