/**
   * This method is required if the AlgorithmPerformed interface is implemented. It is called by the
   * algorithms when it has completed or failed to to complete, so that the dialog can be display
   * the result image and/or clean up.
   *
   * @param algorithm Algorithm that caused the event.
   */
  public void algorithmPerformed(AlgorithmBase algorithm) {

    if (algorithm instanceof AlgorithmNonlocalMeansFilter) {
      image.clearMask();

      if ((nlMeansFilterAlgo.isCompleted() == true) && (resultImage != null)) {

        updateFileInfo(image, resultImage);
        resultImage.clearMask();

        // The algorithm has completed and produced a new image to be displayed.
        try {
          new ViewJFrameImage(resultImage, null, new Dimension(610, 200));
        } catch (OutOfMemoryError error) {
          MipavUtil.displayError("Out of memory: unable to open new frame");
        }
      } else if (resultImage == null) {

        // These next lines set the titles in all frames where the source image is displayed to
        // image name so as to indicate that the image is now unlocked!
        // The image frames are enabled and then registed to the userinterface.
        Vector<ViewImageUpdateInterface> imageFrames = image.getImageFrameVector();

        for (int i = 0; i < imageFrames.size(); i++) {
          ((Frame) (imageFrames.elementAt(i))).setTitle(titles[i]);
          ((Frame) (imageFrames.elementAt(i))).setEnabled(true);

          if (((Frame) (imageFrames.elementAt(i))) != parentFrame) {
            userInterface.registerFrame((Frame) (imageFrames.elementAt(i)));
          }
        }

        if (parentFrame != null) {
          userInterface.registerFrame(parentFrame);
        }

        image.notifyImageDisplayListeners(null, true);
      } else if (resultImage != null) {

        // algorithm failed but result image still has garbage
        resultImage.disposeLocal(); // clean up memory
        resultImage = null;
      }
    }

    if (algorithm.isCompleted()) {
      insertScriptLine();
    }
    // save the completion status for later
    setComplete(algorithm.isCompleted());

    nlMeansFilterAlgo.finalize();
    nlMeansFilterAlgo = null;
    dispose();
  }
  /** Starts the program. */
  public void runAlgorithm() {
    int[] destExtents = null;

    if (srcImage == null) {
      displayError("Source Image is null");

      return;
    }

    if (srcImage.getNDims() == 2) {
      makeKernels2D();
    } else if ((srcImage.getNDims() == 3) && (image25D == false)) {
      makeKernels3D();
    } else if ((srcImage.getNDims() == 3) && (image25D == true)) {
      makeKernels2D();
    }

    try {

      if (srcImage.getNDims() == 2) {
        destExtents = new int[2];
        destExtents[0] = srcImage.getExtents()[0]; // X dim
        destExtents[1] = srcImage.getExtents()[1]; // Y dim
      } else if (srcImage.getNDims() == 3) {
        destExtents = new int[3];
        destExtents[0] = srcImage.getExtents()[0]; // X dim
        destExtents[1] = srcImage.getExtents()[1]; // Y dim
        destExtents[2] = srcImage.getExtents()[2]; // Z dim
      }

      zXMask = new ModelImage(ModelImage.UBYTE, destExtents, " Edges");
    } catch (OutOfMemoryError e) {
      destImage = null;
      srcImage = null;
      zXMask.disposeLocal();
      zXMask = null;
      errorCleanUp("Algorithm EdgeLapSep : Out of memory", true);

      return;
    }

    if (destImage != null) { // NEW

      if (srcImage.getNDims() == 2) {
        calcStoreInDest2D(1, zeroDetectionType);
      } else if ((srcImage.getNDims() == 3) && (image25D == false)) {
        calcStoreInDest3D(zeroDetectionType);
      } else if ((srcImage.getNDims() == 3) && (image25D == true)) {
        calcStoreInDest2D(srcImage.getExtents()[2], zeroDetectionType);
      }
    }

    if (threadStopped) {
      finalize();

      return;
    }
  }
예제 #3
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  /** dispose memory. */
  public void disposeLocal() {

    if (mathAlgo != null) {
      mathAlgo.finalize();
      mathAlgo = null;
    }

    if (image != null) {
      image.disposeLocal();
    }

    image = null;

    if (resultImage != null) {
      resultImage.disposeLocal();
    }

    resultImage = null;
  }
  /**
   * Returns the name of an image output by this algorithm, the image returned depends on the
   * parameter label given (which can be used to retrieve the image object from the image registry).
   *
   * @param imageParamName The output image parameter label for which to get the image name.
   * @return The image name of the requested output image parameter label.
   */
  public String getOutputImageName(final String imageParamName) {
    if (imageParamName.equals(AlgorithmParameters.RESULT_IMAGE)) {
      if (getResultImage() != null) {
        // algo produced a new result image
        return getResultImage().getImageName();
      } else {
        // algo was done in place
        return image.getImageName();
      }
    }

    Preferences.debug(
        "Unrecognized output image parameter: " + imageParamName + "\n",
        Preferences.DEBUG_SCRIPTING);

    return null;
  }
  /** {@inheritDoc} */
  protected void setGUIFromParams() {
    image = scriptParameters.retrieveInputImage();
    userInterface = ViewUserInterface.getReference();
    parentFrame = image.getParentFrame();

    if (scriptParameters.doOutputNewImage()) {
      setDisplayLocNew();
    } else {
      setDisplayLocReplace();
    }

    searchWindowSide = scriptParameters.getParams().getInt("search_window_side");
    similarityWindowSide = scriptParameters.getParams().getInt("similarity_window_side");
    noiseStandardDeviation = scriptParameters.getParams().getFloat("noise_standard_deviation");
    degreeOfFiltering = scriptParameters.getParams().getFloat("degree_of_filtering");
    doRician = scriptParameters.getParams().getBoolean("do_rician");
    image25D = scriptParameters.doProcess3DAs25D();
  }
예제 #6
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  /** {@inheritDoc} */
  protected void setGUIFromParams() {
    image = scriptParameters.retrieveInputImage(1);

    userInterface = ViewUserInterface.getReference();
    parentFrame = image.getParentFrame();

    if (scriptParameters.doOutputNewImage()) {
      setDisplayLocNew();
    } else {

      // replace processing not supported..
      // setDisplayLocReplace();
      setDisplayLocNew();
    }

    subXDim = scriptParameters.getParams().getInt("sub_x_dim");
    subYDim = scriptParameters.getParams().getInt("sub_y_dim");
    numberOfImagesInMosaic = scriptParameters.getParams().getInt("number_of_images_in_mosaic");
  }
  /**
   * Use the GUI results to set up the variables needed to run the algorithm.
   *
   * @return <code>true</code> if parameters set successfully, <code>false</code> otherwise.
   */
  private boolean setVariables() {
    String tmpStr;

    System.gc();

    if (replaceImage.isSelected()) {
      displayLoc = REPLACE;
    } else if (newImage.isSelected()) {
      displayLoc = NEW;
    }

    tmpStr = textSearchWindowSide.getText();

    if (testParameter(tmpStr, 5, 101)) {
      searchWindowSide = Integer.valueOf(tmpStr).intValue();
    } else {
      MipavUtil.displayError("Search window side must be between 5 and 101");
      textSearchWindowSide.requestFocus();
      textSearchWindowSide.selectAll();

      return false;
    }

    if ((searchWindowSide % 2) == 0) {
      MipavUtil.displayError("Search window side must be an odd number");
      textSearchWindowSide.requestFocus();
      textSearchWindowSide.selectAll();
      return false;
    }

    tmpStr = textSimilarityWindowSide.getText();

    if (testParameter(tmpStr, 3, 99)) {
      similarityWindowSide = Integer.valueOf(tmpStr).intValue();
    } else {
      MipavUtil.displayError("Similarity window side must be between 3 and 99");
      textSimilarityWindowSide.requestFocus();
      textSimilarityWindowSide.selectAll();

      return false;
    }

    if ((similarityWindowSide % 2) == 0) {
      MipavUtil.displayError("Similarity window side must be an odd number");
      textSimilarityWindowSide.requestFocus();
      textSimilarityWindowSide.selectAll();
      return false;
    }

    if (similarityWindowSide >= searchWindowSide) {
      MipavUtil.displayError("Similarity window side must be less than search window side");
      textSimilarityWindowSide.requestFocus();
      textSimilarityWindowSide.selectAll();
      return false;
    }

    tmpStr = textNoiseStandardDeviation.getText();

    if (testParameter(tmpStr, 0.001, 1000.0)) {
      noiseStandardDeviation = Float.valueOf(tmpStr).floatValue();
    } else {
      MipavUtil.displayError("Radius must be between 0.001 and 1000.0");
      textNoiseStandardDeviation.requestFocus();
      textNoiseStandardDeviation.selectAll();

      return false;
    }

    doRician = doRicianCheckBox.isSelected();

    if (doRician) {
      tmpStr = textDegree.getText();
      if (testParameter(tmpStr, 1.0, 10.0)) {
        degreeOfFiltering = Float.valueOf(tmpStr).floatValue();
      } else {
        MipavUtil.displayError("Degree of filtering must be between 1.0 and 10.0");
        textDegree.requestFocus();
        textDegree.selectAll();
      }
    }

    if (image.getNDims() > 2) {
      image25D = image25DCheckBox.isSelected();
    }

    return true;
  }
  /**
   * Initializes the GUI by creating the components, placing them in the dialog, and displaying
   * them.
   */
  private void init() {
    setForeground(Color.black);

    setTitle("Nonlocal Means Filter");

    JPanel mainPanel;
    mainPanel = new JPanel();
    mainPanel.setBorder(BorderFactory.createEmptyBorder(3, 3, 3, 3));
    mainPanel.setLayout(new GridBagLayout());

    GridBagConstraints gbc = new GridBagConstraints();
    gbc.gridwidth = 1;
    gbc.gridheight = 1;
    gbc.anchor = GridBagConstraints.WEST;
    gbc.weightx = 1;
    gbc.insets = new Insets(3, 3, 3, 3);
    gbc.gridx = 0;
    gbc.gridy = 0;
    gbc.fill = GridBagConstraints.HORIZONTAL;

    paramPanel = new JPanel(new GridBagLayout());
    paramPanel.setForeground(Color.black);
    paramPanel.setBorder(buildTitledBorder("Parameters"));
    mainPanel.add(paramPanel, gbc);

    GridBagConstraints gbc2 = new GridBagConstraints();
    gbc2.gridwidth = 1;
    gbc2.gridheight = 1;
    gbc2.anchor = GridBagConstraints.WEST;
    gbc2.weightx = 1;
    gbc2.insets = new Insets(3, 3, 3, 3);
    gbc2.gridx = 0;
    gbc2.gridy = 0;
    gbc2.fill = GridBagConstraints.HORIZONTAL;

    labelSearchWindowSide = createLabel("Search window side (odd)");

    paramPanel.add(labelSearchWindowSide, gbc2);

    gbc2.gridx = 1;
    textSearchWindowSide = createTextField("15");
    paramPanel.add(textSearchWindowSide, gbc2);

    gbc2.gridx = 0;
    gbc2.gridy = 1;
    labelSimilarityWindowSide = createLabel("Similarity window side (odd) ");
    paramPanel.add(labelSimilarityWindowSide, gbc2);

    gbc2.gridx = 1;
    textSimilarityWindowSide = createTextField("7");
    paramPanel.add(textSimilarityWindowSide, gbc2);

    gbc2.gridx = 0;
    gbc2.gridy = 2;
    labelNoiseStandardDeviation = createLabel("Noise standard deviation ");
    paramPanel.add(labelNoiseStandardDeviation, gbc2);

    gbc2.gridx = 1;
    textNoiseStandardDeviation = createTextField("10.0");
    paramPanel.add(textNoiseStandardDeviation, gbc2);

    gbc2.gridx = 0;
    gbc2.gridy = 3;
    labelDegree = createLabel("Degree of filtering ");
    labelDegree.setEnabled(doRician);
    paramPanel.add(labelDegree, gbc2);

    gbc2.gridx = 1;
    textDegree = createTextField("1.414");
    textDegree.setEnabled(doRician);
    paramPanel.add(textDegree, gbc2);

    gbc2.gridx = 0;
    gbc2.gridy = 4;
    doRicianCheckBox = new JCheckBox("Deal with Rician noise in MRI");
    doRicianCheckBox.setFont(serif12);
    doRicianCheckBox.setSelected(false);
    doRicianCheckBox.addActionListener(this);
    paramPanel.add(doRicianCheckBox, gbc2);

    if (image.getNDims() > 2) {
      gbc2.gridx = 0;
      gbc2.gridy = 5;
      gbc2.gridwidth = 2;

      image25DCheckBox = new JCheckBox("Process each slice independently (2.5D)");
      image25DCheckBox.setFont(serif12);
      paramPanel.add(image25DCheckBox, gbc2);
      image25DCheckBox.setSelected(false);
    } // if (image.getNDims > 2)

    JPanel outputOptPanel = new JPanel(new GridLayout(1, 2));
    destinationPanel = new JPanel(new BorderLayout());
    destinationPanel.setForeground(Color.black);
    destinationPanel.setBorder(buildTitledBorder("Destination"));
    outputOptPanel.add(destinationPanel);

    destinationGroup = new ButtonGroup();
    newImage = new JRadioButton("New image", true);
    newImage.setBounds(10, 16, 120, 25);
    newImage.setFont(serif12);
    destinationGroup.add(newImage);
    destinationPanel.add(newImage, BorderLayout.NORTH);

    replaceImage = new JRadioButton("Replace image", false);
    replaceImage.setFont(serif12);
    destinationGroup.add(replaceImage);
    destinationPanel.add(replaceImage, BorderLayout.CENTER);

    // Only if the image is unlocked can it be replaced.
    if (image.getLockStatus() == ModelStorageBase.UNLOCKED) {
      replaceImage.setEnabled(true);
    } else {
      replaceImage.setEnabled(false);
    }

    gbc.gridx = 0;
    gbc.gridy = 1;
    mainPanel.add(outputOptPanel, gbc);

    mainDialogPanel.add(mainPanel, BorderLayout.CENTER);
    mainDialogPanel.add(buildButtons(), BorderLayout.SOUTH);

    getContentPane().add(mainDialogPanel);

    pack();
    setResizable(true);
    // setVisible(true);

    System.gc();
  }
  /**
   * Once all the necessary variables are set, call the Nonlocal Means filter algorithm based on
   * what type of image this is and whether or not there is a separate destination image.
   */
  protected void callAlgorithm() {
    String name = makeImageName(image.getImageName(), "_NonlocalMeans");
    int[] destExtents;

    if (image.getNDims() == 2) { // source image is 2D
      destExtents = new int[2];
      destExtents[0] = image.getExtents()[0]; // X dim
      destExtents[1] = image.getExtents()[1]; // Y dim
    } else {
      destExtents = new int[3];
      destExtents[0] = image.getExtents()[0];
      destExtents[1] = image.getExtents()[1];
      destExtents[2] = image.getExtents()[2];
    }

    if (displayLoc == NEW) {

      try {

        // Make result image of float type
        if (image.isColorImage()) {
          resultImage = new ModelImage(ModelImage.ARGB, destExtents, name);
        } else {
          resultImage = new ModelImage(ModelImage.FLOAT, destExtents, name);
        }

        // resultImage = (ModelImage)image.clone();
        // resultImage.setImageName(name);
        // Make algorithm
        nlMeansFilterAlgo =
            new AlgorithmNonlocalMeansFilter(
                resultImage,
                image,
                searchWindowSide,
                similarityWindowSide,
                noiseStandardDeviation,
                degreeOfFiltering,
                doRician,
                image25D);

        // This is very important. Adding this object as a listener allows the algorithm to
        // notify this object when it has completed of failed. See algorithm performed event.
        // This is made possible by implementing AlgorithmedPerformed interface
        nlMeansFilterAlgo.addListener(this);
        createProgressBar(image.getImageName(), nlMeansFilterAlgo);

        // Hide dialog
        setVisible(false);

        if (isRunInSeparateThread()) {

          // Start the thread as a low priority because we wish to still have user interface work
          // fast
          if (nlMeansFilterAlgo.startMethod(Thread.MIN_PRIORITY) == false) {
            MipavUtil.displayError("A thread is already running on this object");
          }
        } else {
          nlMeansFilterAlgo.run();
        }
      } catch (OutOfMemoryError x) {
        MipavUtil.displayError("Dialog Nonlocal Means Filter: unable to allocate enough memory");

        if (resultImage != null) {
          resultImage.disposeLocal(); // Clean up memory of result image
          resultImage = null;
        }

        return;
      }
    } else {

      try {

        // No need to make new image space because the user has choosen to replace the source image
        // Make the algorithm class
        nlMeansFilterAlgo =
            new AlgorithmNonlocalMeansFilter(
                null,
                image,
                searchWindowSide,
                similarityWindowSide,
                noiseStandardDeviation,
                degreeOfFiltering,
                doRician,
                image25D);

        // This is very important. Adding this object as a listener allows the algorithm to
        // notify this object when it has completed of failed. See algorithm performed event.
        // This is made possible by implementing AlgorithmedPerformed interface
        nlMeansFilterAlgo.addListener(this);
        createProgressBar(image.getImageName(), nlMeansFilterAlgo);

        // Hide the dialog since the algorithm is about to run.
        setVisible(false);

        // These next lines set the titles in all frames where the source image is displayed to
        // "locked - " image name so as to indicate that the image is now read/write locked!
        // The image frames are disabled and then unregisted from the userinterface until the
        // algorithm has completed.
        Vector<ViewImageUpdateInterface> imageFrames = image.getImageFrameVector();
        titles = new String[imageFrames.size()];

        for (int i = 0; i < imageFrames.size(); i++) {
          titles[i] = ((Frame) (imageFrames.elementAt(i))).getTitle();
          ((Frame) (imageFrames.elementAt(i))).setTitle("Locked: " + titles[i]);
          ((Frame) (imageFrames.elementAt(i))).setEnabled(false);
          userInterface.unregisterFrame((Frame) (imageFrames.elementAt(i)));
        }

        if (isRunInSeparateThread()) {

          // Start the thread as a low priority because we wish to still have user interface work
          // fast
          if (nlMeansFilterAlgo.startMethod(Thread.MIN_PRIORITY) == false) {
            MipavUtil.displayError("A thread is already running on this object");
          }
        } else {
          nlMeansFilterAlgo.run();
        }
      } catch (OutOfMemoryError x) {
        MipavUtil.displayError("Dialog Nonlocal Means Filter: unable to allocate enough memory");

        return;
      }
    }
  }
  /**
   * This function produces the EdgeLap of input image.
   *
   * @param detectionType the type of zero crossing detection to perform
   */
  private void calcStoreInDest3D(int detectionType) {
    int nImages;
    int length, totalLength;
    float[] buffer, xResultBuffer, yResultBuffer, zResultBuffer;
    int start;
    float[] sliceBuffer;

    try {
      destImage.setLock();
    } catch (IOException error) {
      errorCleanUp("Algorithm EdgeLapSep: Image(s) locked", false);

      return;
    }

    try {
      length = srcImage.getSliceSize();
      totalLength = srcImage.getSliceSize() * srcImage.getExtents()[2];
      nImages = srcImage.getExtents()[2];
      buffer = new float[totalLength];
      sliceBuffer = new float[length];
      srcImage.exportData(0, totalLength, buffer); // locks and releases lock

      // fireProgressStateChanged(srcImage.getImageName(), "Calculating Zero X-ings ...");
    } catch (IOException error) {
      buffer = null;
      sliceBuffer = null;
      xResultBuffer = null;
      yResultBuffer = null;
      zResultBuffer = null;
      errorCleanUp("Algorithm EdgeLapSep exportData: Image(s) locked", true);

      return;
    } catch (OutOfMemoryError e) {
      buffer = null;
      sliceBuffer = null;
      xResultBuffer = null;
      yResultBuffer = null;
      zResultBuffer = null;
      errorCleanUp("Algorithm EdgeLapSep: Out of memory", true);

      return;
    }

    // initProgressBar();
    fireProgressStateChanged(0, srcImage.getImageName(), "Convolving X dimension ...");

    /** Minimum and maximum progress value for the convolving part */
    int min = 0;
    int max = min + Math.round(100 / 2.0f);
    float stepPerDimension = ((float) (max - min)) / 3.0f;
    AlgorithmSeparableConvolver xConvolver = null;

    if (Math.round(stepPerDimension) > 1) {
      xConvolver =
          new AlgorithmSeparableConvolver(
              buffer, srcImage.getExtents(), GxxData, kExtents, false); // assume not color

      xConvolver.setProgressValues(generateProgressValues(min, min + Math.round(stepPerDimension)));
      linkProgressToAlgorithm(xConvolver);
    } else {
      xConvolver =
          new AlgorithmSeparableConvolver(
              buffer, srcImage.getExtents(), GxxData, kExtents, false); // assume not color
    }

    if (!entireImage) {
      xConvolver.setMask(mask);
    }

    xConvolver.run();
    xResultBuffer = xConvolver.getOutputBuffer();
    xConvolver.finalize();
    xConvolver = null;

    fireProgressStateChanged(
        min + Math.round(stepPerDimension), srcImage.getImageName(), "Convolving Y dimension...");

    AlgorithmSeparableConvolver yConvolver = null;

    if ((Math.round(stepPerDimension * 2) - Math.round(stepPerDimension)) > 1) {
      yConvolver =
          new AlgorithmSeparableConvolver(
              buffer, srcImage.getExtents(), GyyData, kExtents, false); // assume not color

      yConvolver.setProgressValues(
          generateProgressValues(
              min + Math.round(stepPerDimension), min + Math.round(stepPerDimension * 2)));

      linkProgressToAlgorithm(yConvolver);
    } else {
      yConvolver =
          new AlgorithmSeparableConvolver(
              buffer, srcImage.getExtents(), GyyData, kExtents, false); // assume not color
    }

    if (!entireImage) {
      yConvolver.setMask(mask);
    }

    yConvolver.run();
    yResultBuffer = yConvolver.getOutputBuffer();
    yConvolver.finalize();
    yConvolver = null;

    fireProgressStateChanged(
        min + Math.round(stepPerDimension * 2),
        srcImage.getImageName(),
        "Convolving Z dimension...");

    AlgorithmSeparableConvolver zConvolver = null;

    if ((Math.round(stepPerDimension * 3) - Math.round(stepPerDimension * 2)) > 1) {
      zConvolver =
          new AlgorithmSeparableConvolver(
              buffer, srcImage.getExtents(), GzzData, kExtents, false); // assume not color

      zConvolver.setProgressValues(
          generateProgressValues(min + Math.round(stepPerDimension * 2), max));

      linkProgressToAlgorithm(zConvolver);
    } else {
      zConvolver =
          new AlgorithmSeparableConvolver(
              buffer, srcImage.getExtents(), GzzData, kExtents, false); // assume not color
    }

    if (!entireImage) {
      zConvolver.setMask(mask);
    }

    zConvolver.run();
    zResultBuffer = zConvolver.getOutputBuffer();
    zConvolver.finalize();
    zConvolver = null;

    min = max;
    max = 100;

    float stepPerImage = ((float) (max - min)) / nImages;

    for (int s = 0; (s < nImages) && !threadStopped; s++) {
      fireProgressStateChanged(
          min + Math.round(stepPerImage * s),
          srcImage.getImageName(),
          "Calculating the edges of slice " + (s + 1) + "...");

      start = s * length;

      for (int i = start; (i < (start + length)) && !threadStopped; i++) {

        if (entireImage || mask.get(i)) {
          destImage.set(i, -(xResultBuffer[i] + yResultBuffer[i] + zResultBuffer[i]));
        } else {
          destImage.set(i, buffer[i]);
        }
      }

      try {
        destImage.exportDataNoLock(start, length, sliceBuffer);
      } catch (IOException error) {
        buffer = null;
        sliceBuffer = null;
        errorCleanUp("Algorithm EdgeLapSep exportData: " + error, true);

        return;
      }

      genZeroXMask(s, sliceBuffer, detectionType);
    }

    if (threadStopped) {
      finalize();

      return;
    }

    zXMask.calcMinMax();
    destImage.calcMinMax();
    destImage.releaseLock();

    setCompleted(true);
  }
  /**
   * This function produces the EdgeLap of input image.
   *
   * @param nImages number of images on which to find zero crossings. If 2D image then nImage = 1.
   *     If 3D image where each image is to processed independently then nImages equals the number
   *     of images in the volume.
   * @param detectionType the type of zero crossing detection to perform
   */
  private void calcStoreInDest2D(int nImages, int detectionType) {

    // int i, s, idx;
    int length;
    int start;
    float[] buffer, xResultBuffer, yResultBuffer;

    try {
      destImage.setLock();
    } catch (IOException error) {
      errorCleanUp("Algorithm EdgeLapSep: Image(s) locked", false);

      return;
    }

    try {
      length = srcImage.getSliceSize();
      buffer = new float[length];
      // fireProgressStateChanged(srcImage.getImageName(), "Calculating the Edge ...");
    } catch (OutOfMemoryError e) {
      buffer = null;
      errorCleanUp("Algorithm Edge Lap Sep: Out of memory", true);

      return;
    }

    fireProgressStateChanged(0, srcImage.getImageName(), "Calculating the Edge ...");

    float stepPerImage = 100f / nImages;

    // initProgressBar();

    for (int s = 0; (s < nImages) && !threadStopped; s++) {
      fireProgressStateChanged(
          Math.round(stepPerImage * s),
          srcImage.getImageName(),
          "Calculating the edges of slice " + (s + 1) + "...");
      start = s * length;

      try {
        srcImage.exportData(start, length, buffer); // locks and releases lock
      } catch (IOException error) {
        errorCleanUp("Algorithm EdgeLapSep: Image(s) locked", false);

        return;
      }

      int min = Math.round(stepPerImage * s);
      int max = min + Math.round(((float) (Math.round(stepPerImage * (s + 1)) - min)) / 2.0f);
      AlgorithmSeparableConvolver xConvolver = null;

      if ((max - min) > 1) {
        xConvolver =
            new AlgorithmSeparableConvolver(
                buffer,
                new int[] {srcImage.getExtents()[0], srcImage.getExtents()[1]},
                GxxData,
                kExtents,
                false);

        xConvolver.setProgressValues(generateProgressValues(min, max));
        linkProgressToAlgorithm(xConvolver);

      } else {
        xConvolver =
            new AlgorithmSeparableConvolver(
                buffer,
                new int[] {srcImage.getExtents()[0], srcImage.getExtents()[1]},
                GxxData,
                kExtents,
                false); // assume not color
      }

      if (!entireImage) {
        xConvolver.setMask(mask);
      }

      xConvolver.run();
      xResultBuffer = xConvolver.getOutputBuffer();
      xConvolver.finalize();
      xConvolver = null;

      min = max;
      max = Math.round(stepPerImage * (s + 1));

      AlgorithmSeparableConvolver yConvolver = null;

      if ((max - min) > 1) {
        yConvolver =
            new AlgorithmSeparableConvolver(
                buffer,
                new int[] {srcImage.getExtents()[0], srcImage.getExtents()[1]},
                GyyData,
                kExtents,
                false);

        yConvolver.setProgressValues(generateProgressValues(min, max));
        linkProgressToAlgorithm(yConvolver);

      } else {
        yConvolver =
            new AlgorithmSeparableConvolver(
                buffer,
                new int[] {srcImage.getExtents()[0], srcImage.getExtents()[1]},
                GyyData,
                kExtents,
                false); // assume not color
      }

      if (!entireImage) {
        yConvolver.setMask(mask);
      }

      yConvolver.run();
      yResultBuffer = yConvolver.getOutputBuffer();
      yConvolver.finalize();
      yConvolver = null;

      for (int i = 0, idx = start; (i < buffer.length) && !threadStopped; i++, idx++) {

        if (entireImage || mask.get(i)) {
          destImage.set(idx, -(xResultBuffer[i] + yResultBuffer[i]));
        } else {
          destImage.set(idx, buffer[i]);
        }
      }

      try {
        destImage.exportDataNoLock(start, length, buffer);
      } catch (IOException error) {
        errorCleanUp("Algorithm EdgeLapSep exportData: " + error, false);

        return;
      }

      genZeroXMask(s, buffer, detectionType);
    }

    if (threadStopped) {
      finalize();

      return;
    }

    zXMask.calcMinMax();
    destImage.calcMinMax();
    destImage.releaseLock();

    setCompleted(true);
  }
  /**
   * Generates a zero crossing mask for a 2D function. Sets a ModelImage to 255 if a zero crossing
   * is detected.
   *
   * @param slice the slice of the volume which we are working on (0 if from 2D image)
   * @param buffer array in which to find zero crossing
   * @param detectionType the type of zero crossing detection to perform
   */
  public void genZeroXMask(int slice, float[] buffer, int detectionType) {
    float x0, x1, x2, x3;
    int i0, i1, i2, i3;
    int i, j;
    int indexY;
    int length;

    int xDim = srcImage.getExtents()[0];
    int yDim = srcImage.getExtents()[1];

    length = xDim * yDim;

    int xxDim = xDim - 1;
    int yyDim = yDim - 1;
    float level = 0;
    int offset = slice * length;

    for (j = 0; j < yyDim; j++) {
      indexY = j * xDim;

      for (i = 0; i < xxDim; i++) {
        i0 = indexY + i;

        if (detectionType == MARCHING_SQUARES) {
          i1 = i0 + 1;
          i2 = i0 + xDim;
          i3 = i0 + 1 + xDim;

          x0 = buffer[i0];
          x1 = buffer[i1];
          x2 = buffer[i2];
          x3 = buffer[i3];

          if ((x0 >= level)
              && (x1 >= level)
              && (x2 >= level)
              && (x3 >= level)) { // case 0 - no edge
          } else if ((x0 >= level) && (x1 >= level) && (x2 < level) && (x3 >= level)) {

            // case 1 - edge in the lower left
            zXMask.set(offset + i2, 255);
          } else if ((x0 >= level) && (x1 >= level) && (x2 >= level) && (x3 < level)) {

            // case 2 - edge in the lower right
            zXMask.set(offset + i3, 255);
          } else if ((x0 >= level) && (x1 >= level) && (x2 < level) && (x3 < level)) {

            // case 3 - edge horizontally
            zXMask.set(offset + i2, 255);
            zXMask.set(offset + i3, 255);
          } else if ((x0 >= level) && (x1 < level) && (x2 >= level) && (x3 >= level)) {

            // case 4 - edge in the upper right
            zXMask.set(offset + i1, 255);
          } else if ((x0 >= level) && (x1 < level) && (x2 < level) && (x3 >= level)) {

            // case 5 - ambiguous case; either edge in upper right and lower left or
            // edge that goes from the upper right to the lower left
            zXMask.set(offset + i1, 255);
            zXMask.set(offset + i2, 255);
          } else if ((x0 >= level) && (x1 < level) && (x2 >= level) && (x3 < level)) {

            // case 6 - edge going vertically along the right
            zXMask.set(offset + i1, 255);
            zXMask.set(offset + i3, 255);
          } else if ((x0 >= level) && (x1 < level) && (x2 < level) && (x3 < level)) {

            // case 7 - edge in the upper left
            zXMask.set(offset + i0, 255);
          } else if ((x0 < level) && (x1 >= level) && (x2 >= level) && (x3 >= level)) {

            // case 8 - edge in the upper left
            zXMask.set(offset + i0, 255);
          } else if ((x0 < level) && (x1 >= level) && (x2 < level) && (x3 >= level)) {

            // case 9 - edge going vertically along the left
            zXMask.set(offset + i0, 255);
            zXMask.set(offset + i2, 255);
          } else if ((x0 < level) && (x1 >= level) && (x2 >= level) && (x3 < level)) {

            // case 10 - ambiguous case; either edge in upper left and lower right or
            // edge that goes from the upper left to the lower right
            zXMask.set(offset + i0, 255);
            zXMask.set(offset + i3, 255);
          } else if ((x0 < level) && (x1 >= level) && (x2 < level) && (x3 < level)) {

            // case 11 - edge in the upper right
            zXMask.set(offset + i1, 255);
          } else if ((x0 < level) && (x1 < level) && (x2 >= level) && (x3 >= level)) {

            // case 12 - edge going horizontally along the top
            zXMask.set(offset + i0, 255);
            zXMask.set(offset + i1, 255);
          } else if ((x0 < level) && (x1 < level) && (x2 < level) && (x3 >= level)) {

            // case 13 - edge in the lower right
            zXMask.set(offset + i3, 255);
          } else if ((x0 < level) && (x1 < level) && (x2 >= level) && (x3 < level)) {

            // case 14 - edge in the lower left
            zXMask.set(offset + i2, 255);
          } else if ((x0 < level)
              && (x1 < level)
              && (x2 < level)
              && (x3 < level)) { // case 15 - no edge
          }
        } else if (detectionType == NEGATIVE_EDGES) {

          if (buffer[i0] <= 1) {
            zXMask.set(offset + i0, 255);
          }
        } else if (detectionType == OLD_DETECTION) {
          i1 = i0 + 1;
          i2 = i0 + xDim;
          i3 = i0 + 1 + xDim;

          x0 = buffer[i0];
          x1 = buffer[i1];
          x2 = buffer[i2];
          x3 = buffer[i3];

          if ((x0 > level) && (x1 > level) && (x2 > level) && (x3 > level)) {
            zXMask.set(offset + i0, 0);
          } else if ((x0 < level) && (x1 < level) && (x2 < level) && (x3 < level)) {
            zXMask.set(offset + i0, 0);
          } else {
            zXMask.set(offset + i0, 255);
          }
        }
      }
    }

    FileInfoBase[] fileInfo = zXMask.getFileInfo();

    fileInfo[slice].setModality(srcImage.getFileInfo()[slice].getModality());
    fileInfo[slice].setFileDirectory(srcImage.getFileInfo()[slice].getFileDirectory());
    fileInfo[slice].setEndianess(srcImage.getFileInfo()[slice].getEndianess());
    fileInfo[slice].setUnitsOfMeasure(srcImage.getFileInfo()[slice].getUnitsOfMeasure());
    fileInfo[slice].setResolutions(srcImage.getFileInfo()[slice].getResolutions());
    fileInfo[slice].setExtents(zXMask.getExtents());
    fileInfo[slice].setMax(255);
    fileInfo[slice].setMin(0);
    fileInfo[slice].setPixelPadValue(srcImage.getFileInfo()[slice].getPixelPadValue());
    fileInfo[slice].setPhotometric(srcImage.getFileInfo()[slice].getPhotometric());
  }
예제 #13
0
  /**
   * Use the GUI results to set up the variables needed to run the algorithm.
   *
   * @return <code>true</code> if parameters set successfully, <code>false</code> otherwise.
   */
  private boolean setVariables() {
    String tmpStr;

    tmpStr = textXDim.getText();
    try {
      subXDim = Integer.parseInt(tmpStr);
    } catch (NumberFormatException e) {
      MipavUtil.displayError("New XDIM string is not a valid integer");
      textXDim.requestFocus();
      textXDim.selectAll();

      return false;
    }
    if (subXDim < 3) {
      MipavUtil.displayError("New XDIM must be at least 3");
      textXDim.requestFocus();
      textXDim.selectAll();

      return false;
    } else if (subXDim > image.getExtents()[0]) {
      MipavUtil.displayError("New XDIM cannot exceed " + image.getExtents()[0]);
      textXDim.requestFocus();
      textXDim.selectAll();

      return false;
    }

    tmpStr = textYDim.getText();
    try {
      subYDim = Integer.parseInt(tmpStr);
    } catch (NumberFormatException e) {
      MipavUtil.displayError("New YDIM string is not a valid integer");
      textYDim.requestFocus();
      textYDim.selectAll();

      return false;
    }
    if (subYDim < 3) {
      MipavUtil.displayError("New YDIM must be at least 3");
      textYDim.requestFocus();
      textYDim.selectAll();

      return false;
    } else if (subYDim > image.getExtents()[1]) {
      MipavUtil.displayError("New YDIM cannot exceed " + image.getExtents()[1]);
      textYDim.requestFocus();
      textYDim.selectAll();

      return false;
    }

    tmpStr = textNumberImages.getText();
    try {
      numberOfImagesInMosaic = Integer.parseInt(tmpStr);
    } catch (NumberFormatException e) {
      MipavUtil.displayError("New numberOfImagesInMosaic string is not a valid integer");
      textNumberImages.requestFocus();
      textNumberImages.selectAll();

      return false;
    }
    if (numberOfImagesInMosaic < 1) {
      MipavUtil.displayError("New numberOfImagesInMosaic must be at least 1");
      textNumberImages.requestFocus();
      textNumberImages.selectAll();

      return false;
    } else if (numberOfImagesInMosaic > (subXDim * subYDim)) {
      MipavUtil.displayError("New numberOfImagesInMosaic cannot exceed (newXDim) * (newYDim)");
      textNumberImages.requestFocus();
      textNumberImages.selectAll();

      return false;
    }

    displayLoc = NEW;

    return true;
  }
예제 #14
0
  /** Sets up the GUI (panels, buttons, etc) and displays it on the screen. */
  private void init() {
    if (image.getFileInfo(0).getFileFormat() == FileUtility.DICOM) {
      FileInfoDicom dicomInfo = (FileInfoDicom) image.getFileInfo(0);
      FileDicomTagTable tagTable = dicomInfo.getTagTable();
      if (tagTable.getValue("0018,1310") != null) {
        // Acquisition matrix
        FileDicomTag tag = tagTable.get(new FileDicomKey("0018,1310"));
        Object[] values = tag.getValueList();
        int valNumber = values.length;
        if ((valNumber == 4) && (values instanceof Short[])) {
          int frequencyRows = ((Short) values[0]).intValue();
          Preferences.debug("frequencyRows = " + frequencyRows + "\n");
          int frequencyColumns = ((Short) values[1]).intValue();
          Preferences.debug("frequencyColumns = " + frequencyColumns + "\n");
          int phaseRows = ((Short) values[2]).intValue();
          Preferences.debug("phaseRows = " + phaseRows + "\n");
          int phaseColumns = ((Short) values[3]).intValue();
          Preferences.debug("phaseColumns = " + phaseColumns + "\n");
          if ((frequencyRows > 0) && (phaseRows == 0)) {
            subYDim = frequencyRows;
          } else if ((frequencyRows == 0) && (phaseRows > 0)) {
            subYDim = phaseRows;
          }
          if ((frequencyColumns > 0) && (phaseColumns == 0)) {
            subXDim = frequencyColumns;
          } else if ((frequencyColumns == 0) && (phaseColumns > 0)) {
            subXDim = phaseColumns;
          }
        }
      } // if (tagTable.getValue("0018,1310") != null)
      if (tagTable.getValue("0019,100A") != null) {
        FileDicomTag tag = tagTable.get(new FileDicomKey("0019,100A"));
        Object value = tag.getValue(false);
        if (value instanceof Short) {
          numberOfImagesInMosaic = ((Short) value).intValue();
          Preferences.debug("Number of images in mosaic = " + numberOfImagesInMosaic + "\n");
        }
      } // if (tagTable.getValue("0019,100A") != null)
    } // if (image.getFileInfo(0).getFileFormat() == FileUtility.DICOM)*/
    setForeground(Color.black);
    setTitle("Mosaic To 3D Volume");

    JPanel inputPanel = new JPanel(new GridBagLayout());
    inputPanel.setForeground(Color.black);

    inputPanel.setBorder(buildTitledBorder("Image"));

    JLabel labelUse = new JLabel("Image:");
    labelUse.setForeground(Color.black);
    labelUse.setFont(serif12);

    JLabel labelImage = new JLabel(image.getImageName());
    labelImage.setForeground(Color.black);
    labelImage.setFont(serif12);

    GridBagConstraints gbc = new GridBagConstraints();
    gbc.gridx = 0;
    gbc.gridy = 0;
    gbc.gridheight = 1;
    gbc.gridwidth = 1;
    gbc.anchor = GridBagConstraints.WEST;
    gbc.weightx = 1;
    gbc.insets = new Insets(5, 5, 5, 5);
    inputPanel.add(labelUse, gbc);
    gbc.gridx = 1;
    gbc.fill = GridBagConstraints.HORIZONTAL;
    inputPanel.add(labelImage, gbc);

    JPanel dimensionPanel = new JPanel(new GridBagLayout());
    dimensionPanel.setForeground(Color.black);
    dimensionPanel.setBorder(buildTitledBorder("X and Y Dimensions of Result"));

    JLabel labelXDim = new JLabel("X dimension of slices");
    labelXDim.setForeground(Color.black);
    labelXDim.setFont(serif12);

    textXDim = new JTextField(10);
    if (subXDim != 0) {
      textXDim.setText(String.valueOf(subXDim));
    }
    textXDim.setFont(serif12);
    textXDim.setForeground(Color.black);

    JLabel labelYDim = new JLabel("Y dimension of slices");
    labelYDim.setForeground(Color.black);
    labelYDim.setFont(serif12);

    textYDim = new JTextField(10);
    if (subYDim != 0) {
      textYDim.setText(String.valueOf(subYDim));
    }
    textYDim.setFont(serif12);
    textYDim.setForeground(Color.black);

    JLabel labelNumberImages = new JLabel("Number of images in mosaic");
    labelNumberImages.setForeground(Color.black);
    labelNumberImages.setFont(serif12);

    textNumberImages = new JTextField(10);
    if (numberOfImagesInMosaic != 0) {
      textNumberImages.setText(String.valueOf(numberOfImagesInMosaic));
    }
    textNumberImages.setFont(serif12);
    textNumberImages.setForeground(Color.black);

    gbc.gridx = 0;
    gbc.gridy = 0;
    dimensionPanel.add(labelXDim, gbc);
    gbc.gridx = 1;
    dimensionPanel.add(textXDim, gbc);
    gbc.gridx = 0;
    gbc.gridy = 1;
    dimensionPanel.add(labelYDim, gbc);
    gbc.gridx = 1;
    dimensionPanel.add(textYDim, gbc);
    gbc.gridx = 0;
    gbc.gridy = 2;
    dimensionPanel.add(labelNumberImages, gbc);
    gbc.gridx = 1;
    dimensionPanel.add(textNumberImages, gbc);

    JPanel mainPanel = new JPanel(new BorderLayout());
    mainPanel.add(inputPanel, BorderLayout.NORTH);
    mainPanel.add(dimensionPanel, BorderLayout.CENTER);
    mainPanel.setBorder(BorderFactory.createEmptyBorder(5, 5, 5, 5));

    JPanel buttonPanel = new JPanel();
    buttonPanel.add(buildButtons());

    getContentPane().add(mainPanel);
    getContentPane().add(buttonPanel, BorderLayout.SOUTH);
    pack();
    setVisible(true);
  }
예제 #15
0
  /**
   * Once all the necessary variables are set, call the Concat algorithm based on what type of image
   * this is and whether or not there is a separate destination image.
   */
  protected void callAlgorithm() {
    int destExtents[] = new int[3];
    ModelImage destImage = null;

    destExtents[0] = subXDim;
    destExtents[1] = subYDim;
    destExtents[2] = numberOfImagesInMosaic;

    destImage =
        new ModelImage(
            image.getType(), destExtents, makeImageName(image.getImageName(), "_mosaic_to_slices"));

    try {

      // Make algorithm
      mathAlgo = new AlgorithmMosaicToSlices(image, destImage);

      // This is very important. Adding this object as a listener allows the algorithm to
      // notify this object when it has completed of failed. See algorithm performed event.
      // This is made possible by implementing AlgorithmedPerformed interface
      mathAlgo.addListener(this);

      createProgressBar(image.getImageName(), mathAlgo);

      // Hide dialog
      setVisible(false);

      if (displayLoc == REPLACE) {

        // These next lines set the titles in all frames where the source image is displayed to
        // "locked - " image name so as to indicate that the image is now read/write locked!
        // The image frames are disabled and then unregisted from the userinterface until the
        // algorithm has completed.
        Vector<ViewImageUpdateInterface> imageFrames = image.getImageFrameVector();
        titles = new String[imageFrames.size()];

        for (int i = 0; i < imageFrames.size(); i++) {
          titles[i] = ((Frame) (imageFrames.elementAt(i))).getTitle();
          ((Frame) (imageFrames.elementAt(i))).setTitle("Locked: " + titles[i]);
          ((Frame) (imageFrames.elementAt(i))).setEnabled(false);
          userInterface.unregisterFrame((Frame) (imageFrames.elementAt(i)));
        }
      }

      if (isRunInSeparateThread()) {

        // Start the thread as a low priority because we wish to still have user interface work
        // fast.
        if (mathAlgo.startMethod(Thread.MIN_PRIORITY) == false) {
          MipavUtil.displayError("A thread is already running on this object");
        }

      } else {

        mathAlgo.run();
      }
    } catch (OutOfMemoryError x) {
      System.gc();
      MipavUtil.displayError("Dialog Concatenation: unable to allocate enough memory");

      return;
    }
  }
예제 #16
0
  /**
   * This method is required if the AlgorithmPerformed interface is implemented. It is called by the
   * algorithms when it has completed or failed to to complete, so that the dialog can be display
   * the result image and/or clean up.
   *
   * @param algorithm Algorithm that caused the event.
   */
  public void algorithmPerformed(AlgorithmBase algorithm) {
    ViewJFrameImage imageFrame = null;

    if (algorithm instanceof AlgorithmMosaicToSlices) {

      if ((mathAlgo.isCompleted() == true) && (mathAlgo.getResultImage() != null)) {

        // The algorithm has completed and produced a new image to be displayed.
        if (displayLoc == NEW) {

          try {
            resultImage = mathAlgo.getResultImage();

            new ViewJFrameImage(resultImage, null, new Dimension(610, 200));
          } catch (OutOfMemoryError error) {
            System.gc();
            MipavUtil.displayError("Out of memory: unable to open new frame");
          }
        } else {

          // These next lines set the titles in all frames where the source image is displayed to
          // image name so as to indicate that the image is now unlocked!
          // The image frames are enabled and then registed to the userinterface.
          resultImage = mathAlgo.getResultImage();

          Vector<ViewImageUpdateInterface> imageFrames = image.getImageFrameVector();

          for (int i = 0; i < imageFrames.size(); i++) {
            ((Frame) (imageFrames.elementAt(i))).setTitle(titles[i]);
            ((Frame) (imageFrames.elementAt(i))).setEnabled(true);

            if ((((Frame) (imageFrames.elementAt(i))) != parentFrame) && (parentFrame != null)) {
              userInterface.registerFrame((Frame) (imageFrames.elementAt(i)));
            }
          }

          Point pt;

          if (parentFrame != null) {
            pt = ((ViewJFrameBase) parentFrame).getLocation();
          } else {
            pt =
                new Point(
                    Toolkit.getDefaultToolkit().getScreenSize().width / 2,
                    Toolkit.getDefaultToolkit().getScreenSize().height / 2);
          }

          imageFrame = new ViewJFrameImage(resultImage, null, new Dimension(pt.x, pt.y));

          if (parentFrame != null) {
            ((ViewJFrameBase) parentFrame).close();
          } else {
            ((ViewJFrameBase) image.getParentFrame()).close();
          }

          // Not so sure about this.
          if (image.getLightBoxFrame() != null) {

            try {
              pt = image.getLightBoxFrame().getLocation();
              image.getLightBoxFrame().close();
              new ViewJFrameLightBox(
                  imageFrame,
                  "LightBox",
                  resultImage,
                  imageFrame.getComponentImage().getLUTa(),
                  imageFrame.getComponentImage().getImageB(),
                  imageFrame.getComponentImage().getLUTb(),
                  imageFrame.getComponentImage().getResolutionX(),
                  imageFrame.getComponentImage().getResolutionY(),
                  new Dimension(pt.x, pt.y),
                  imageFrame.getControls(),
                  imageFrame.getVOIManager());
            } catch (OutOfMemoryError error) {
              MipavUtil.displayError("Out of memory: unable to open new frame");
            }
          }
        }
      } else if (resultImage == null) {

        // These next lines set the titles in all frames where the source image is displayed to
        // image name so as to indicate that the image is now unlocked!
        // The image frames are enabled and then registered to the userinterface.
        /*Vector imageFrames = imageA.getImageFrameVector();

        for (int i = 0; i < imageFrames.size(); i++) {
            ((Frame) (imageFrames.elementAt(i))).setTitle(titles[i]);
            ((Frame) (imageFrames.elementAt(i))).setEnabled(true);

            if (((Frame) (imageFrames.elementAt(i))) != parentFrame) {
                userInterface.registerFrame((Frame) (imageFrames.elementAt(i)));

            }
        }*/

        if (parentFrame != null) {
          userInterface.registerFrame(parentFrame);
        }

        image.notifyImageDisplayListeners(null, true);
      } else if (resultImage != null) {

        // algorithm failed but result image still has garbage
        resultImage.disposeLocal(); // clean up memory
        System.gc();
      }
    }

    if (algorithm.isCompleted()) {
      insertScriptLine();
    }

    mathAlgo.finalize();
    mathAlgo = null;
    dispose();
  }