Examples with ObjectCentre uk.ac.sussex.gdsc.ij.foci.ObjectAnalyzer.ObjectCentre used on opensource projects

Example 1 with ObjectCentre

use of uk.ac.sussex.gdsc.ij.foci.ObjectAnalyzer.ObjectCentre in project gdsc by aherbert.

the class NucleiOutline_PlugIn method divideLargeObjects.

/**
 * Divide objects that are too large. If any objects were divided then the original object mask is
 * updated in-place and returned.
 *
 * @param bp the original object mask
 * @param oa the object analyzer
 * @param maxPixelCount the maximum size in pixels for an object
 * @return the updated object mask (or null)
 */
private static ByteProcessor divideLargeObjects(ByteProcessor bp, ObjectAnalyzer oa, int maxPixelCount) {
    final int maxObject = oa.getMaxObject();
    final ObjectCentre[] objectData = oa.getObjectCentres();
    // Divide those that are too large
    final IntArrayList toDivide = new IntArrayList();
    for (int i = 1; i <= maxObject; i++) {
        if (objectData[i].getSize() > maxPixelCount) {
            toDivide.add(i);
        }
    }
    if (!toDivide.isEmpty()) {
        final int[] mask = oa.getObjectMask();
        final byte[] original = (byte[]) bp.getPixels();
        final byte[] tmp = new byte[mask.length];
        // Move each object to divide from the original to a temp image
        toDivide.forEach(object -> {
            for (int i = 0; i < mask.length; i++) {
                if (mask[i] == object) {
                    original[i] = 0;
                    tmp[i] = (byte) 255;
                }
            }
        });
        // Watershed the new temp image
        final EDM edm = new EDM();
        final ByteProcessor tmpIp = new ByteProcessor(bp.getWidth(), bp.getHeight(), tmp);
        // The watershed respects the ImageJ setting for Binary processor inversion based on
        // the input ImagePlus. Here it is null and so no need to invert.
        edm.setup("watershed", null);
        edm.run(tmpIp);
        IJ.showStatus("");
        // Re-create the objects
        bp.copyBits(tmpIp, 0, 0, Blitter.ADD);
        return bp;
    }
    return null;
}

Example 2 with ObjectCentre

use of uk.ac.sussex.gdsc.ij.foci.ObjectAnalyzer.ObjectCentre in project gdsc by aherbert.

the class FrapAnalysis_PlugIn method extractBleachedRegions.

private LocalList<Pair<Integer, Roi>> extractBleachedRegions(final ImageStack events) {
    // Post-process the events to join contiguous regions and remove speckles
    IJ.showStatus("!Extracting bleached regions...");
    final LocalList<Pair<Integer, Roi>> rois = new LocalList<>();
    for (int i = 1; i <= events.size(); i++) {
        final ByteProcessor bp = (ByteProcessor) events.getProcessor(i);
        // Find objects in each frame
        final ObjectAnalyzer oa = new ObjectAnalyzer(bp);
        oa.setMinObjectSize(settings.minRegionSize);
        if (oa.getMaxObject() != 0) {
            ImageJUtils.log("Detected %s on frame %d:", TextUtils.pleural(oa.getMaxObject(), "region"), i);
            final Roi[] outlines = oa.getObjectOutlines();
            final ObjectCentre[] centres = oa.getObjectCentres();
            for (int j = 1; j < outlines.length; j++) {
                ImageJUtils.log("  [%d] (%.2f,%.2f) = %s pixels", j, intersect.x + centres[j].getCentreX(), intersect.y + centres[j].getCentreY(), centres[j].getSize());
                // Store 0-based index for the bleaching event
                rois.add(Pair.create(i - 1, outlines[j]));
            }
        }
    }
    IJ.protectStatusBar(false);
    return rois;
}

Example 3 with ObjectCentre

use of uk.ac.sussex.gdsc.ij.foci.ObjectAnalyzer.ObjectCentre in project gdsc by aherbert.

the class AssignFociToObjects_PlugIn method run.

/**
 * {@inheritDoc}
 */
@Override
public void run(ImageProcessor ip) {
    if (!showDialog()) {
        return;
    }
    final ArrayList<Search[]> searchGrid = createDistanceGrid(settings.radius);
    createResultsTables();
    final ObjectAnalyzer oa = new ObjectAnalyzer(ip);
    if (settings.removeSmallObjects) {
        oa.setMinObjectSize(settings.minSize);
    }
    oa.setEightConnected(settings.eightConnected);
    final int[] objectMask = oa.getObjectMask();
    final int maxx = ip.getWidth();
    final int maxy = ip.getHeight();
    final double maxD2 = settings.radius * settings.radius;
    // Assign each foci to the nearest object
    final int[] count = new int[oa.getMaxObject() + 1];
    final int[] found = new int[results.size()];
    final double[] d2 = new double[found.length];
    Arrays.fill(d2, -1);
    for (int i = 0; i < results.size(); i++) {
        final int[] result = results.get(i);
        final int x = result[0];
        final int y = result[1];
        // Check within the image
        if (x < 0 || x >= maxx || y < 0 || y >= maxy) {
            continue;
        }
        int index = y * maxx + x;
        if (objectMask[index] != 0) {
            count[objectMask[index]]++;
            found[i] = objectMask[index];
            d2[i] = 0;
            continue;
        }
        // Search for the closest object(s)
        final int[] closestCount = new int[count.length];
        // Scan wider and wider from 0,0 until we find an object.
        for (final Search[] next : searchGrid) {
            if (next[0].d2 > maxD2) {
                break;
            }
            boolean ok = false;
            for (final Search s : next) {
                final int xx = x + s.x;
                final int yy = y + s.y;
                if (xx < 0 || xx >= maxx || yy < 0 || yy >= maxy) {
                    continue;
                }
                index = yy * maxx + xx;
                if (objectMask[index] != 0) {
                    ok = true;
                    closestCount[objectMask[index]]++;
                }
            }
            if (ok) {
                // Get the object with the highest count
                int maxCount = 0;
                for (int j = 1; j < closestCount.length; j++) {
                    if (closestCount[maxCount] < closestCount[j]) {
                        maxCount = j;
                    }
                }
                // Assign
                count[maxCount]++;
                found[i] = maxCount;
                d2[i] = next[0].d2;
                break;
            }
        }
    }
    final ObjectCentre[] centres = oa.getObjectCentres();
    // We must ignore those that are too small/big
    final int[] idMap = new int[count.length];
    for (int i = 1; i < count.length; i++) {
        idMap[i] = i;
        if (centres[i].getSize() < settings.minSize || (settings.maxSize != 0 && centres[i].getSize() > settings.maxSize)) {
            idMap[i] = -i;
        }
    }
    // TODO - Remove objects from the output image ?
    showMask(oa, found, idMap);
    // Show the results
    final DescriptiveStatistics stats = new DescriptiveStatistics();
    final DescriptiveStatistics stats2 = new DescriptiveStatistics();
    final StringBuilder sb = new StringBuilder();
    for (int i = 1, j = 0; i < count.length; i++) {
        sb.append(imp.getTitle());
        sb.append('\t').append(i);
        sb.append('\t').append(MathUtils.rounded(centres[i].getCentreX()));
        sb.append('\t').append(MathUtils.rounded(centres[i].getCentreY()));
        sb.append('\t').append(centres[i].getSize());
        if (idMap[i] > 0) {
            // Include this object
            sb.append("\tTrue");
            stats.addValue(count[i]);
        } else {
            // Exclude this object
            sb.append("\tFalse");
            stats2.addValue(count[i]);
        }
        sb.append('\t').append(count[i]);
        sb.append('\n');
        // Flush before 10 lines to ensure auto-layout of columns
        if (i >= 9 && j++ == 0) {
            resultsWindow.append(sb.toString());
            sb.setLength(0);
        }
    }
    resultsWindow.append(sb.toString());
    // Histogram the count
    if (settings.showHistogram) {
        final int max = (int) stats.getMax();
        final double[] xvalues = new double[max + 1];
        final double[] yvalues = new double[xvalues.length];
        for (int i = 1; i < count.length; i++) {
            if (idMap[i] > 0) {
                yvalues[count[i]]++;
            }
        }
        double ymax = 0;
        for (int i = 0; i <= max; i++) {
            xvalues[i] = i;
            if (ymax < yvalues[i]) {
                ymax = yvalues[i];
            }
        }
        final String title = TITLE + " Histogram";
        final Plot plot = new Plot(title, "Count", "Frequency");
        plot.addPoints(xvalues, yvalues, Plot.LINE);
        plot.setLimits(0, xvalues[xvalues.length - 1], 0, ymax);
        plot.addLabel(0, 0, String.format("N = %d, Mean = %s", (int) stats.getSum(), MathUtils.rounded(stats.getMean())));
        plot.draw();
        plot.setColor(Color.RED);
        plot.drawLine(stats.getMean(), 0, stats.getMean(), ymax);
        ImageJUtils.display(title, plot);
    }
    // Show the summary
    sb.setLength(0);
    sb.append(imp.getTitle());
    sb.append('\t').append(oa.getMaxObject());
    sb.append('\t').append(stats.getN());
    sb.append('\t').append(results.size());
    sb.append('\t').append((int) stats.getSum());
    sb.append('\t').append((int) stats2.getSum());
    sb.append('\t').append(results.size() - (int) (stats.getSum() + stats2.getSum()));
    sb.append('\t').append(stats.getMin());
    sb.append('\t').append(stats.getMax());
    sb.append('\t').append(MathUtils.rounded(stats.getMean()));
    sb.append('\t').append(MathUtils.rounded(stats.getPercentile(50)));
    sb.append('\t').append(MathUtils.rounded(stats.getStandardDeviation()));
    summaryWindow.append(sb.toString());
    if (!settings.showDistances) {
        return;
    }
    sb.setLength(0);
    for (int i = 0, j = 0; i < results.size(); i++) {
        final int[] result = results.get(i);
        final int x = result[0];
        final int y = result[1];
        // Check within the image
        if (x < 0 || x >= maxx || y < 0 || y >= maxy) {
            continue;
        }
        sb.append(imp.getTitle());
        sb.append('\t').append(i + 1);
        sb.append('\t').append(x);
        sb.append('\t').append(y);
        if (found[i] > 0) {
            sb.append('\t').append(found[i]);
            if (idMap[found[i]] > 0) {
                sb.append("\tTrue\t");
            } else {
                sb.append("\tFalse\t");
            }
            sb.append(MathUtils.rounded(Math.sqrt(d2[i])));
            sb.append('\n');
        } else {
            sb.append("\t\t\t\n");
        }
        // Flush before 10 lines to ensure auto-layout of columns
        if (i >= 9 && j++ == 0) {
            distancesWindow.append(sb.toString());
            sb.setLength(0);
        }
    }
    distancesWindow.append(sb.toString());
}

Example 4 with ObjectCentre

use of uk.ac.sussex.gdsc.ij.foci.ObjectAnalyzer.ObjectCentre in project gdsc by aherbert.

the class ObjectAnalyzerTest method checkGetObjectCentres.

@Test
void checkGetObjectCentres() {
    final int maxx = 4;
    final int maxy = 3;
    final byte[] image = { // @formatter:off
    0, 0, 3, 4, 0, 3, 0, 0, 0, 3, 7, 7 };
    // @formatter:on
    final ObjectAnalyzer oa = new ObjectAnalyzer(new ByteProcessor(maxx, maxy, image));
    oa.getMaxObject();
    final ObjectCentre[] centres = { // @formatter:off
    null, new ObjectCentre(2, 0, 1), new ObjectCentre(3, 0, 1), new ObjectCentre(1, 1.5, 2), new ObjectCentre(2.5, 2, 2) };
    // @formatter:on
    Assertions.assertArrayEquals(centres, oa.getObjectCentres());
}