/**
* 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;
}
}
/** 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();
}
/** {@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());
}
/**
* 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;
}
/** 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);
}
/**
* 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;
}
}
/**
* 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();
}
