コード例 #1
0
  /** Calls the algorithm. */
  protected void callAlgorithm() {

    try {
      resultImage =
          new ModelImage(imageA.getType(), imageA.getExtents(), (imageA.getImageName() + "_isn"));
      resultImage.copyFileTypeInfo(imageA);

      // Make algorithm
      isnAlgo = new PlugInAlgorithmISN(resultImage, imageA);

      // 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
      isnAlgo.addListener(this);

      createProgressBar(imageA.getImageName(), " ...", isnAlgo);

      // Hide dialog
      setVisible(false);

      if (isRunInSeparateThread()) {

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

      return;
    }
  }
コード例 #2
0
  /** Starts the program. */
  public void runAlgorithm() {
    int i, j, k;

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

      return;
    }

    if (threadStopped) {
      finalize();

      return;
    }

    trueVOIs = srcImage.getVOIs();
    nTrueVOIs = trueVOIs.size();
    testVOIs = testImage.getVOIs();
    nTestVOIs = testVOIs.size();
    length = srcImage.getExtents()[0];

    for (i = 1; i < srcImage.getNDims(); i++) {
      length *= srcImage.getExtents()[i];
    }

    testLength = testImage.getExtents()[0];

    for (i = 1; i < testImage.getNDims(); i++) {
      testLength *= testImage.getExtents()[i];
    }

    if (length != testLength) {
      MipavUtil.displayError(
          srcImage.getImageName()
              + " and "
              + testImage.getImageName()
              + " are unequal in dimensions");
      setCompleted(false);

      return;
    }

    trueMask = new short[length];
    testMask = new short[length];
    ViewUserInterface.getReference().setGlobalDataText(srcImage.getImageName() + " = true\n");
    ViewUserInterface.getReference().setGlobalDataText(testImage.getImageName() + " = test\n");

    for (i = 0; i < nTrueVOIs; i++) {

      if ((trueVOIs.VOIAt(i).getCurveType() == VOI.CONTOUR)
          || (trueVOIs.VOIAt(i).getCurveType() == VOI.POLYLINE)) {
        trueID = trueVOIs.VOIAt(i).getID();

        for (j = 0; j < nTestVOIs; j++) {
          testID = testVOIs.VOIAt(j).getID();

          if (trueID == testID) {

            for (k = 0; k < length; k++) {
              trueMask[k] = -1;
              testMask[k] = -1;
            }

            trueMask = srcImage.generateVOIMask(trueMask, i);
            testMask = testImage.generateVOIMask(testMask, j);
            absoluteTrue = 0;
            trueFound = 0;
            falseNegative = 0;
            falsePositive = 0;

            for (k = 0; k < length; k++) {

              if (trueMask[k] == trueID) {
                absoluteTrue++;

                if (testMask[k] == trueID) {
                  trueFound++;
                } else {
                  falseNegative++;
                }
              } // if (trueMask[k] == trueID)
              else { // trueMask[k] != trueID

                if (testMask[k] == trueID) {
                  falsePositive++;
                }
              } // else trueMask[k] != trueID
            } // for (k = 0; k < length; k++)

            ViewUserInterface.getReference()
                .setGlobalDataText(
                    "Statistics for VOIs with ID = " + String.valueOf(trueID) + "\n");
            fnvf = (float) falseNegative / (float) absoluteTrue;
            ViewUserInterface.getReference()
                .setGlobalDataText(
                    "     False negative volume fraction = " + String.valueOf(fnvf) + "\n");
            fpvf = (float) falsePositive / (float) absoluteTrue;
            ViewUserInterface.getReference()
                .setGlobalDataText(
                    "     False positive volume fraction = " + String.valueOf(fpvf) + "\n");
            tpvf = (float) trueFound / (float) absoluteTrue;
            ViewUserInterface.getReference()
                .setGlobalDataText(
                    "     True Positive volume fraction = " + String.valueOf(tpvf) + "\n\n");
          } // if (trueID == testID)
        } // for (j = 0; j < nTestVOIs; j++)
      } // if ((trueVOIs.VOIAt(i).getCurveType() == VOI.CONTOUR)
    } // for (i = 0; i < nTrueVOIs; i++)

    setCompleted(true);
  }
コード例 #3
0
  /**
   * 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;
      }
    }
  }
コード例 #4
0
ファイル: AlgorithmBase.java プロジェクト: shirley9073/mipav
  /**
   * Working ... This function is never used. It doesn't modify any parameters or data members and
   * returns void.
   *
   * @param image DOCUMENT ME!
   * @param doColor DOCUMENT ME!
   */
  public void calculatePrincipleAxis(ModelImage image, boolean doColor) {
    int x, y, z;
    int n = 0;
    Matrix3f mat2 = new Matrix3f(); // Row,Col
    Matrix3f meanProduct = new Matrix3f();
    Vector3f mean = new Vector3f(); // Column vector
    double voxVal = 0;
    double total = 0;
    double tot = 0;

    // Moments first and second order
    double mX = 0, mY = 0, mZ = 0, mXX = 0, mXY = 0, mXZ = 0, mYY = 0, mYZ = 0, mZZ = 0;

    float min = (float) image.getMin();

    int xEnd = image.getExtents()[0];
    int yEnd = image.getExtents()[1];
    int zEnd = image.getExtents()[2];

    int nLim = (int) Math.sqrt((double) xEnd * yEnd * zEnd);

    if (nLim < 1000) {
      nLim = 1000;
    }

    for (z = 0; z < zEnd; z++) {

      for (y = 0; y < yEnd; y++) {

        for (x = 0; x < xEnd; x++) {

          if (doColor) {
            voxVal =
                (double)
                    (image.getFloatC(x, y, z, 1)
                        + image.getFloatC(x, y, z, 2)
                        + image.getFloatC(x, y, z, 3));
          } else {
            voxVal = (double) (image.getFloat(x, y, z) - min);
          }

          mX += voxVal * x;
          mY += voxVal * y;
          mZ += voxVal * z;
          mXX += voxVal * x * x;
          mXY += voxVal * x * y;
          mXZ += voxVal * x * z;
          mYY += voxVal * y * y;
          mYZ += voxVal * y * z;
          mZZ += voxVal * z * z;
          tot += voxVal;
          n++;

          if (n > nLim) { // Lets not over run the buffers during summation
            n = 0;
            total += tot;
            mat2.M00 = (float) (mat2.M00 + mXX);
            mat2.M01 = (float) (mat2.M01 + mXY);
            mat2.M02 = (float) (mat2.M02 + mXZ);
            mat2.M11 = (float) (mat2.M11 + mYY);
            mat2.M12 = (float) (mat2.M12 + mYZ);
            mat2.M22 = (float) (mat2.M22 + mZZ);
            mean.X = (float) (mean.X + mX);
            mean.Y = (float) (mean.Y + mY);
            mean.Z = (float) (mean.Z + mZ);
            tot = 0;
            mX = 0;
            mY = 0;
            mZ = 0;
            mXX = 0;
            mXY = 0;
            mXZ = 0;
            mYY = 0;
            mYZ = 0;
            mZZ = 0;
          }
        }
      }
    }

    total += tot;

    if (Math.abs(total) < 1e-5) {
      total = 1.0f;
    }

    mat2.M00 = (float) ((mat2.M00 + mXX) / total);
    mat2.M01 = (float) ((mat2.M01 + mXY) / total);
    mat2.M02 = (float) ((mat2.M02 + mXZ) / total);
    mat2.M11 = (float) ((mat2.M11 + mYY) / total);
    mat2.M12 = (float) ((mat2.M12 + mYZ) / total);
    mat2.M22 = (float) ((mat2.M22 + mZZ) / total);
    mean.X = (float) ((mean.X + mX) / total);
    mean.Y = (float) ((mean.Y + mY) / total);
    mean.Z = (float) ((mean.Z + mZ) / total);

    // Now make it central (taking off the Center of Mass)
    meanProduct.MakeTensorProduct(mean, mean);
    mat2.M00 -= meanProduct.M00;
    mat2.M01 -= meanProduct.M01;
    mat2.M02 -= meanProduct.M02;
    mat2.M10 -= meanProduct.M10;
    mat2.M11 -= meanProduct.M11;
    mat2.M12 -= meanProduct.M12;
    mat2.M20 -= meanProduct.M20;
    mat2.M21 -= meanProduct.M21;
    mat2.M22 -= meanProduct.M22;
  }
コード例 #5
0
  /**
   * 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());
  }
コード例 #6
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;
    int i;

    int totLength = image.getExtents()[0];

    for (i = 1; i < image.getNDims(); i++) {
      totLength *= image.getExtents()[i];
    }

    tmpStr = greenMergingText.getText();
    mergingDistance = Float.parseFloat(tmpStr);
    if (mergingDistance < 0.0f) {
      MipavUtil.displayError("Merging distance cannot be less than 0");
      greenMergingText.requestFocus();
      greenMergingText.selectAll();
      return false;
    }

    tmpStr = redMinText.getText();
    redMin = Integer.parseInt(tmpStr);

    if (redMin < 1) {
      MipavUtil.displayError("red minimum must be at least 1");
      redMinText.requestFocus();
      redMinText.selectAll();

      return false;
    } else if (redMin > totLength) {
      MipavUtil.displayError("red minimum must not exceed " + totLength);
      redMinText.requestFocus();
      redMinText.selectAll();

      return false;
    }

    tmpStr = redFractionText.getText();
    redFraction = Float.parseFloat(tmpStr);

    if (redFraction <= 0.0f) {
      MipavUtil.displayError("red fraction must be greater than zero");
      redFractionText.requestFocus();
      redFractionText.selectAll();

      return false;
    } else if (redFraction > 1.0f) {
      MipavUtil.displayError("red fraction must not exceed one");
      redFractionText.requestFocus();
      redFractionText.selectAll();

      return false;
    }

    tmpStr = greenMinText.getText();
    greenMin = Integer.parseInt(tmpStr);

    if (greenMin < 1) {
      MipavUtil.displayError("green minimum must be at least 1");
      greenMinText.requestFocus();
      greenMinText.selectAll();

      return false;
    } else if (greenMin > totLength) {
      MipavUtil.displayError("green minimum must not exceed " + totLength);
      greenMinText.requestFocus();
      greenMinText.selectAll();

      return false;
    }

    tmpStr = greenFractionText.getText();
    greenFraction = Float.parseFloat(tmpStr);

    if (greenFraction <= 0.0f) {
      MipavUtil.displayError("green fraction must be greater than zero");
      greenFractionText.requestFocus();
      greenFractionText.selectAll();

      return false;
    } else if (greenFraction > 1.0f) {
      MipavUtil.displayError("green fraction must not exceed one");
      greenFractionText.requestFocus();
      greenFractionText.selectAll();

      return false;
    }

    tmpStr = blueMinText.getText();
    blueMin = Integer.parseInt(tmpStr);
    if (blueMin <= 0) {
      MipavUtil.displayError("Number of blue pixels must be greater than 0");
      blueMinText.requestFocus();
      blueMinText.selectAll();
      return false;
    } else if (blueMin > totLength) {
      MipavUtil.displayError("blue minimum must not exceed " + totLength);
      blueMinText.requestFocus();
      blueMinText.selectAll();

      return false;
    }

    if (oneButton.isSelected()) {
      greenRegionNumber = 1;
    } else if (twoButton.isSelected()) {
      greenRegionNumber = 2;
    } else if (threeButton.isSelected()) {
      greenRegionNumber = 3;
    } else {
      greenRegionNumber = 4;
    }

    twoGreenLevels = twoBox.isSelected();

    tmpStr = blueValueText.getText();
    blueBoundaryFraction = Float.parseFloat(tmpStr);
    if (blueBoundaryFraction < 0.0f) {
      MipavUtil.displayError("Blue boundary fraction cannot be less than 0.0");
      blueValueText.requestFocus();
      blueValueText.selectAll();
      return false;
    } else if (blueBoundaryFraction > 1.0f) {
      MipavUtil.displayError("Blue boundary value cannot be greater than 1.0");
      blueValueText.requestFocus();
      blueValueText.selectAll();
      return false;
    }

    blueSmooth = blueSmoothBox.isSelected();

    tmpStr = interpolationText.getText();
    interpolationDivisor = Float.parseFloat(tmpStr);
    if (interpolationDivisor <= 1.0f) {
      MipavUtil.displayError("Interpolation divisor must be greater than 1");
      interpolationText.requestFocus();
      interpolationText.selectAll();
      return false;
    }

    return true;
  } // end setVariables()
コード例 #7
0
  /** cat. */
  private void cat3D_4D_4D() {

    int length;
    int xDim, yDim;
    float[] buffer;
    int cFactor = 1;
    int i, j;
    float[] resols = new float[3];
    float[] origins = new float[3];
    FileInfoBase[] fileInfo = null;
    FileInfoDicom[] fileInfoDicom = null;
    int srcALength, srcBLength;

    try {
      fireProgressStateChanged(srcImage1.getImageName(), "Concatenating images ...");
      resols = new float[4];
      origins = new float[4];
      xDim = srcImage1.getExtents()[0];
      yDim = srcImage1.getExtents()[1];

      if (srcImage1.isColorImage()) {
        cFactor = 4;
      }

      length = cFactor * xDim * yDim;
      buffer = new float[length];

      int nImages;

      if (srcImage1.getNDims() > srcImage2.getNDims()) {
        nImages =
            (srcImage1.getExtents()[2] * srcImage1.getExtents()[3]) + srcImage2.getExtents()[2];

        for (i = 0;
            (i < (srcImage1.getExtents()[2] * srcImage1.getExtents()[3])) && !threadStopped;
            i++) {
          fireProgressStateChanged(Math.round((float) (i) / (nImages - 1) * 100));

          srcImage1.exportData(i * length, length, buffer);
          destImage.importData(i * length, buffer, false);
        }

        if (threadStopped) {
          buffer = null;
          finalize();

          return;
        }

        for (j = 0; (j < srcImage2.getExtents()[2]) && !threadStopped; j++) {
          fireProgressStateChanged(Math.round((float) (i + j) / (nImages - 1) * 100));

          srcImage2.exportData(j * length, length, buffer);
          destImage.importData((i + j) * length, buffer, false);
        }

        if (threadStopped) {
          buffer = null;
          finalize();

          return;
        }

        destImage.calcMinMax();
      } else {
        nImages =
            (srcImage2.getExtents()[2] * srcImage2.getExtents()[3]) + srcImage1.getExtents()[2];

        for (j = 0; (j < srcImage1.getExtents()[2]) && !threadStopped; j++) {
          fireProgressStateChanged(Math.round((float) (j) / (nImages - 1) * 100));

          srcImage1.exportData(j * length, length, buffer);
          destImage.importData(j * length, buffer, false);
        }

        if (threadStopped) {
          buffer = null;
          finalize();

          return;
        }

        for (i = 0;
            (i < (srcImage2.getExtents()[2] * srcImage2.getExtents()[3])) && !threadStopped;
            i++) {
          fireProgressStateChanged(Math.round((float) (i + j) / (nImages - 1) * 100));

          srcImage2.exportData(i * buffer.length, length, buffer);
          destImage.importData((i + j) * buffer.length, buffer, false);
        }

        if (threadStopped) {
          buffer = null;
          finalize();

          return;
        }

        destImage.calcMinMax();
      }
    } catch (IOException error) {
      buffer = null;
      destImage.disposeLocal(); // Clean up memory of result image
      destImage = null;
      errorCleanUp("Algorithm Concat. Images: Image(s) locked", true);

      return;
    } catch (OutOfMemoryError e) {
      buffer = null;
      destImage.disposeLocal(); // Clean up memory of result image
      destImage = null;
      errorCleanUp("Algorithm Concat. Images: Out of memory", true);

      return;
    }

    resols[0] = srcImage1.getFileInfo()[0].getResolutions()[0];
    resols[1] = srcImage1.getFileInfo()[0].getResolutions()[1];
    resols[2] = srcImage1.getFileInfo()[0].getResolutions()[2];
    resols[3] = srcImage1.getFileInfo()[0].getResolutions()[3];
    origins[0] = srcImage1.getFileInfo()[0].getOrigin()[0];
    origins[1] = srcImage1.getFileInfo()[0].getOrigin()[1];
    origins[2] = srcImage1.getFileInfo()[0].getOrigin()[2];
    origins[3] = srcImage1.getFileInfo()[0].getOrigin()[3];

    if ((srcImage1.getFileInfo()[0] instanceof FileInfoDicom)
        && (srcImage2.getFileInfo()[0] instanceof FileInfoDicom)) {
      fileInfoDicom = new FileInfoDicom[destImage.getExtents()[2] * destImage.getExtents()[3]];

      if (srcImage1.getNDims() > srcImage2.getNDims()) {
        srcALength = srcImage1.getExtents()[2] * srcImage1.getExtents()[3];

        for (i = 0; (i < srcALength) && !threadStopped; i++) {
          fileInfoDicom[i] = (FileInfoDicom) (((FileInfoDicom) srcImage1.getFileInfo()[i]).clone());
          fileInfoDicom[i].setOrigin(origins);
        }

        for (i = 0; (i < srcImage2.getExtents()[2]) && !threadStopped; i++) {
          fileInfoDicom[srcALength + i] =
              (FileInfoDicom) (((FileInfoDicom) srcImage2.getFileInfo()[i]).clone());
          fileInfoDicom[srcALength + i].setOrigin(origins);
        }
      } else {
        srcBLength = srcImage2.getExtents()[2] * srcImage2.getExtents()[3];

        for (i = 0; (i < srcImage1.getExtents()[2]) && !threadStopped; i++) {
          fileInfoDicom[i] = (FileInfoDicom) (((FileInfoDicom) srcImage1.getFileInfo()[i]).clone());
          fileInfoDicom[i].setOrigin(origins);
        }

        for (i = 0; (i < srcBLength) && !threadStopped; i++) {
          fileInfoDicom[srcImage1.getExtents()[2] + i] =
              (FileInfoDicom) (((FileInfoDicom) srcImage2.getFileInfo()[i]).clone());
          fileInfoDicom[srcImage1.getExtents()[2] + i].setOrigin(origins);
        }
      }

      destImage.setFileInfo(fileInfoDicom);
    } else {
      fileInfo = destImage.getFileInfo();

      for (i = 0;
          (i < (destImage.getExtents()[2] * destImage.getExtents()[3])) && !threadStopped;
          i++) {
        fileInfo[i].setModality(srcImage1.getFileInfo()[0].getModality());
        fileInfo[i].setFileDirectory(srcImage1.getFileInfo()[0].getFileDirectory());
        fileInfo[i].setEndianess(srcImage1.getFileInfo()[0].getEndianess());
        fileInfo[i].setUnitsOfMeasure(srcImage1.getFileInfo()[0].getUnitsOfMeasure());
        fileInfo[i].setResolutions(resols);
        fileInfo[i].setExtents(destImage.getExtents());
        fileInfo[i].setMax(destImage.getMax());
        fileInfo[i].setMin(destImage.getMin());
        fileInfo[i].setImageOrientation(srcImage1.getImageOrientation());
        fileInfo[i].setPixelPadValue(srcImage1.getFileInfo()[0].getPixelPadValue());
        fileInfo[i].setPhotometric(srcImage1.getFileInfo()[0].getPhotometric());
        fileInfo[i].setAxisOrientation(srcImage1.getAxisOrientation());
      }

      if (srcImage1.getFileInfo()[0] instanceof FileInfoImageXML) {

        if (srcImage1.getNDims() > srcImage2.getNDims()) {
          srcALength = srcImage1.getExtents()[2] * srcImage1.getExtents()[3];

          for (i = 0; (i < srcALength) && !threadStopped; i++) {

            if (((FileInfoImageXML) srcImage1.getFileInfo()[i]).getPSetHashtable() != null) {
              ((FileInfoImageXML) fileInfo[i])
                  .setPSetHashtable(
                      ((FileInfoImageXML) srcImage1.getFileInfo()[i]).getPSetHashtable());
            }
          }
        } else {

          for (i = 0; (i < srcImage1.getExtents()[2]) && !threadStopped; i++) {

            if (((FileInfoImageXML) srcImage1.getFileInfo()[i]).getPSetHashtable() != null) {
              ((FileInfoImageXML) fileInfo[i])
                  .setPSetHashtable(
                      ((FileInfoImageXML) srcImage1.getFileInfo()[i]).getPSetHashtable());
            }
          }
        }
      }

      if (srcImage2.getFileInfo()[0] instanceof FileInfoImageXML) {

        if (srcImage1.getNDims() > srcImage2.getNDims()) {
          srcALength = srcImage1.getExtents()[2] * srcImage1.getExtents()[3];

          for (i = 0; (i < srcImage2.getExtents()[2]) && !threadStopped; i++) {

            if (((FileInfoImageXML) srcImage2.getFileInfo()[i]).getPSetHashtable() != null) {
              ((FileInfoImageXML) fileInfo[srcALength + i])
                  .setPSetHashtable(
                      ((FileInfoImageXML) srcImage2.getFileInfo()[i]).getPSetHashtable());
            }
          }

        } else {
          srcBLength = srcImage2.getExtents()[2] * srcImage2.getExtents()[3];

          for (i = 0; (i < srcBLength) && !threadStopped; i++) {

            if (((FileInfoImageXML) srcImage2.getFileInfo()[i]).getPSetHashtable() != null) {
              ((FileInfoImageXML) fileInfo[srcImage1.getExtents()[2] + i])
                  .setPSetHashtable(
                      ((FileInfoImageXML) srcImage2.getFileInfo()[i]).getPSetHashtable());
            }
          }
        }
      }
    }

    if (threadStopped) {
      buffer = null;
      finalize();

      return;
    }

    setCompleted(true);
    fileInfo = null;
    fileInfoDicom = null;
  }
コード例 #8
0
  /**
   * This function produces a new image that has been concatenated. Two 2D-images become one 3D
   * image.
   */
  private void cat2D_2D_3D() {

    int length;
    int xDim, yDim;
    int i;
    float[] buffer;
    int cFactor = 1;
    float[] resols = new float[3];
    FileInfoBase[] fileInfo = null;
    FileInfoDicom[] fileInfoDicom = null;

    try {
      resols = new float[3];
      xDim = srcImage1.getExtents()[0];
      yDim = srcImage1.getExtents()[1];

      if (srcImage1.isColorImage()) {
        cFactor = 4;
      }

      length = cFactor * xDim * yDim;
      buffer = new float[length];
      srcImage1.exportData(0, length, buffer);
      destImage.importData(0, buffer, false);
      srcImage2.exportData(0, length, buffer);
      destImage.importData(buffer.length, buffer, true);
    } catch (IOException error) {
      buffer = null;
      destImage.disposeLocal(); // Clean up memory of result image
      destImage = null;
      errorCleanUp("Algorithm Concat. Images: Image(s) locked", true);

      return;
    } catch (OutOfMemoryError e) {
      buffer = null;
      destImage.disposeLocal(); // Clean up memory of result image
      destImage = null;
      errorCleanUp("Algorithm Concat. Images: Out of memory", true);

      return;
    }

    resols[0] = srcImage1.getFileInfo()[0].getResolutions()[0];
    resols[1] = srcImage1.getFileInfo()[0].getResolutions()[1];
    resols[2] = 1;

    if ((srcImage1.getFileInfo()[0] instanceof FileInfoDicom)
        && (srcImage2.getFileInfo()[0] instanceof FileInfoDicom)) {
      fileInfoDicom = new FileInfoDicom[destImage.getExtents()[2]];
      fileInfoDicom[0] = (FileInfoDicom) (((FileInfoDicom) srcImage1.getFileInfo()[0]).clone());
      fileInfoDicom[1] = (FileInfoDicom) (((FileInfoDicom) srcImage2.getFileInfo()[0]).clone());
      destImage.setFileInfo(fileInfoDicom);
    } else {
      fileInfo = destImage.getFileInfo();

      for (i = 0; (i < destImage.getExtents()[2]) && !threadStopped; i++) {
        fileInfo[i].setModality(srcImage1.getFileInfo()[0].getModality());
        fileInfo[i].setFileDirectory(srcImage1.getFileInfo()[0].getFileDirectory());
        fileInfo[i].setEndianess(srcImage1.getFileInfo()[0].getEndianess());
        fileInfo[i].setUnitsOfMeasure(srcImage1.getFileInfo()[0].getUnitsOfMeasure());
        fileInfo[i].setResolutions(resols);
        fileInfo[i].setExtents(destImage.getExtents());
        fileInfo[i].setMax(destImage.getMax());
        fileInfo[i].setMin(destImage.getMin());
        fileInfo[i].setImageOrientation(srcImage1.getImageOrientation());
        fileInfo[i].setPixelPadValue(srcImage1.getFileInfo()[0].getPixelPadValue());
        fileInfo[i].setPhotometric(srcImage1.getFileInfo()[0].getPhotometric());
        fileInfo[i].setAxisOrientation(srcImage1.getAxisOrientation());
      }

      if (srcImage1.getFileInfo()[0] instanceof FileInfoImageXML) {

        if (((FileInfoImageXML) srcImage1.getFileInfo()[0]).getPSetHashtable() != null) {
          ((FileInfoImageXML) fileInfo[0])
              .setPSetHashtable(((FileInfoImageXML) srcImage1.getFileInfo()[0]).getPSetHashtable());
        }
      }

      if (srcImage2.getFileInfo()[0] instanceof FileInfoImageXML) {

        if (((FileInfoImageXML) srcImage2.getFileInfo()[0]).getPSetHashtable() != null) {
          ((FileInfoImageXML) fileInfo[1])
              .setPSetHashtable(((FileInfoImageXML) srcImage2.getFileInfo()[0]).getPSetHashtable());
        }
      }
    }

    if (threadStopped) {
      buffer = null;
      finalize();

      return;
    }

    setCompleted(true);

    fileInfo = null;
    fileInfoDicom = null;
  }
コード例 #9
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;
  }