Java tutorial
/* * To change this license header, choose License Headers in Project Properties. * To change this template file, choose Tools | Templates * and open the template in the editor. */ package oct.analysis.application.comp; import java.awt.Point; import java.awt.image.BufferedImage; import java.util.ArrayList; import java.util.LinkedList; import java.util.List; import java.util.Map; import java.util.OptionalInt; import java.util.concurrent.ExecutionException; import java.util.logging.Level; import java.util.logging.Logger; import java.util.stream.Collectors; import java.util.stream.IntStream; import java.util.stream.Stream; import javax.swing.JOptionPane; import javax.swing.SwingWorker; import oct.analysis.application.OCTLine; import oct.analysis.application.dat.Cardinality; import oct.analysis.application.dat.EZEdgeCoord; import oct.analysis.application.dat.LinePoint; import oct.analysis.application.dat.OCTAnalysisManager; import oct.analysis.application.dat.SelectionLRPManager; import oct.analysis.application.dat.SelectionType; import oct.util.Segmentation; import oct.util.Util; import oct.util.ip.SharpenOperation; import org.apache.commons.math3.analysis.UnivariateFunction; import org.apache.commons.math3.analysis.interpolation.LoessInterpolator; import org.apache.commons.math3.analysis.interpolation.UnivariateInterpolator; import org.apache.commons.math3.exception.OutOfRangeException; /** * * @author Brandon M. Wilk {@literal <}wilkb777@gmail.com{@literal >} */ public class EZWorker extends SwingWorker<EZEdgeCoord, Point> { private final OCTAnalysisManager analysisManager = OCTAnalysisManager.getInstance(); private final SelectionLRPManager selMngr = SelectionLRPManager.getInstance(); private final boolean debug = false; private final int debug_sleep = 50; private final int depthThreshold = 6000; @Override protected EZEdgeCoord doInBackground() throws Exception { int foveaCenterXPosition = analysisManager.getFoveaCenterXPosition(); /* first get a sharpened version of the OCT and use that to obtain the segmentation of the Bruch's membrane. Use a Loess interpolation algorithm to smooth out imperfetions in the segmentation line. */ UnivariateInterpolator interpolator = new LoessInterpolator(0.1, 0); ArrayList<Point> rawBrmPoints = new ArrayList<>(analysisManager .getSegmentation(new SharpenOperation(15, 0.5F)).getSegment(Segmentation.BrM_SEGMENT)); double[][] brmSeg = Util.getXYArraysFromPoints(rawBrmPoints); UnivariateFunction brmInterp = interpolator.interpolate(brmSeg[0], brmSeg[1]); BufferedImage sharpOCT = analysisManager.getSharpenedOctImage(8.5D, 1.0F); setProgress(10); /* Starting from the identified location of the fovea search northward in the image until the most northern pixels northward (in a 3x3 matrix of pixels arround the the search point (X,Y) ) are black (ie. the search matrix is has found that the search point isn't totally surrounded by white pixels). Then a recursive search algorithm determines if the black area signifies the seperation between bands or simply represents a closed (a black blob entirely surrounded by white pixels) black band. It will continue searching northward in the image until it can find an open region of all blak pixels. Once this is found it will find the contour of the edge between the black and white pixels along the width of the image. */ int searchY = (int) Math.round(brmInterp.value(foveaCenterXPosition)) + 1; do { searchY--; } while (Util.calculateGrayScaleValue(sharpOCT.getRGB(foveaCenterXPosition, searchY)) > 0 || !isContrastPoint(foveaCenterXPosition, searchY, sharpOCT)); LinkedList<Point> contour = new LinkedList<>(); Point startPoint = new Point(foveaCenterXPosition, searchY); //find contour by searching for white pixel boundary to te right of the fovea contour.add(findContourRight(startPoint, Cardinality.SOUTH, startPoint, Cardinality.SOUTH, contour, sharpOCT, 0)); //search until open black area found (ie. if the search algorithm arrives back at //the starting pixel keep moving north to next black area to search) while (contour.get(0).equals(startPoint)) { contour = new LinkedList<>(); do { searchY--; } while (Util.calculateGrayScaleValue(sharpOCT.getRGB(foveaCenterXPosition, searchY)) == 0); do { searchY--; } while (Util.calculateGrayScaleValue(sharpOCT.getRGB(foveaCenterXPosition, searchY)) > 0 || isSurroundedByWhite(foveaCenterXPosition, searchY, sharpOCT)); startPoint = new Point(foveaCenterXPosition, searchY); contour.add(findContourRight(startPoint, Cardinality.SOUTH, startPoint, Cardinality.SOUTH, contour, sharpOCT, 0)); } setProgress(20); //open balck space found, complete contour to left of fovea contour.add( findContourLeft(startPoint, Cardinality.SOUTH, startPoint, Cardinality.SOUTH, contour, sharpOCT)); analysisManager.getImgPanel().setDrawPoint(new Point(foveaCenterXPosition, searchY)); setProgress(30); /* since the contour can snake around due to aberations and low image density we need to create a single line (represented by points) from left to right to represent the countour. This is easily done by building a line of points consisting of the point with the largest Y value (furthest from the top of the image) at each X value. This eliminates overhangs from the contour line. */ Map<Double, List<Point>> grouped = contour.stream().collect(Collectors.groupingBy(Point::getX)); List<Point> refinedEZContour = grouped.values().stream().map((List<Point> points) -> { int maxY = points.stream().mapToInt((Point p) -> p.y).min().getAsInt(); return new Point(points.get(0).x, maxY); }).sorted((Point p1, Point p2) -> Integer.compare(p1.x, p2.x)).collect(Collectors.toList()); setProgress(35); /* Starting from the identified location of the fovea search southward in the image until the most southern pixels (in a 3x3 matrix of pixels arround the the search point (X,Y) ) are black (ie. the search matrix has found that the search point isn't totally surrounded by white pixels). Then a recursive search algorithm determines if the black area signifies the bottom of the Bruch's membrane or simply represents a closed (a black blob entirely surrounded by white pixels) black band. It will continue searching southward in the image until it can find an open region of all black pixels. Once this is found it will find the contour of the edge between the black and white pixels, along the width of the image, of the bottom of the Bruch's membrane. */ // sharpOCT = getSharpenedOctImage(5D, 1.0F); searchY = (int) Math.round(brmInterp.value(foveaCenterXPosition)); do { searchY++; } while (Util.calculateGrayScaleValue(sharpOCT.getRGB(foveaCenterXPosition, searchY)) > 0 || isSurroundedByWhite(foveaCenterXPosition, searchY, sharpOCT)); contour = new LinkedList<>(); startPoint = new Point(foveaCenterXPosition, searchY); /* Find contour by searching for white pixel boundary to te right of the fovea. Sometimes the crap below the Bruchs membrane causes too much interferance for the algorithm to work properly so we must tweak some of the parameters of the sharpening performed on the image until the algorithm succedes or we can no longer tweak parameters. In the case of the later event we can use the raw segmented Bruchs membrane as a substitute to keep the method from failing. */ contour.add(findContourRight(startPoint, Cardinality.NORTH, startPoint, Cardinality.NORTH, contour, sharpOCT, 0)); double filtValue = 8.5D; boolean tweakFailed = false; while (contour.contains(null)) { contour = new LinkedList<>(); filtValue -= 0.5D; System.out.println("Reducing sigma to " + filtValue); if (filtValue <= 0D) { tweakFailed = true; break; } sharpOCT = analysisManager.getSharpenedOctImage(8.5D, 1.0F); contour.add(findContourRight(startPoint, Cardinality.NORTH, startPoint, Cardinality.NORTH, contour, sharpOCT, 0)); } if (tweakFailed) { contour = new LinkedList<>(rawBrmPoints); } else { //search until open black area found (ie. if the search algorithm arrives back at //the starting pixel keep moving south to next black area to search) while (contour.get(0).equals(startPoint)) { contour = new LinkedList<>(); do { searchY++; } while (Util.calculateGrayScaleValue(sharpOCT.getRGB(foveaCenterXPosition, searchY)) == 0); do { searchY++; } while (Util.calculateGrayScaleValue(sharpOCT.getRGB(foveaCenterXPosition, searchY)) > 0 || isSurroundedByWhite(foveaCenterXPosition, searchY, sharpOCT)); startPoint = new Point(foveaCenterXPosition, searchY); contour.add(findContourRight(startPoint, Cardinality.NORTH, startPoint, Cardinality.NORTH, contour, sharpOCT, 0)); } setProgress(45); //open balck space found, complete contour to left of fovea contour.add(findContourLeft(startPoint, Cardinality.NORTH, startPoint, Cardinality.NORTH, contour, sharpOCT)); } setProgress(55); /* since the contour can snake around due to aberations and low image density we need to create a single line (represented by points) from left to right to represent the countour. This is easily done by building a line of points consisting of the point with the smallest Y value (closest to the top of the image) at each X value. This eliminates overhangs from the contour line. */ grouped = contour.stream().collect(Collectors.groupingBy(Point::getX)); List<Point> refinedBruchsMembraneContour = grouped.values().stream().map((List<Point> points) -> { int minY = points.stream().mapToInt((Point p) -> p.y).min().getAsInt(); return new Point(points.get(0).x, minY); }).sorted((Point p1, Point p2) -> Integer.compare(p1.x, p2.x)).collect(Collectors.toList()); setProgress(70); /* use a Loess interpolator again to smooth the new contours of the EZ and Bruch's Membrane */ double[][] refinedContourPoints = Util.getXYArraysFromPoints(refinedEZContour); UnivariateFunction interpEZContour = interpolator.interpolate(refinedContourPoints[0], refinedContourPoints[1]); refinedContourPoints = Util.getXYArraysFromPoints(refinedBruchsMembraneContour); UnivariateFunction interpBruchsContour = interpolator.interpolate(refinedContourPoints[0], refinedContourPoints[1]); /* find the average difference in the distance in the Y between the 10 pixels at each end of the Bruch's Membrane contour and the contour created along the top of the EZ. */ //since the lines are sorted on X position it is easy to align the lines //based on the tails of each line int minX = refinedEZContour.get(0).x; int maxX; //the interpolator can shorten the range of the X values from the original supplied //so we need to test where the end of the range occurs since it isn't directly accessible for (maxX = refinedEZContour.get(refinedEZContour.size() - 1).x; maxX > minX; maxX--) { try { double tmp = interpEZContour.value(maxX) - interpBruchsContour.value(maxX); //if this break is reached we have found the max value the interpolators will allow break; } catch (OutOfRangeException oe) { //do nothing but let loop continue } } double avgDif = Stream .concat(IntStream.range(minX + 30, minX + 50).boxed(), IntStream.range(maxX - 49, maxX - 28).boxed()) .mapToDouble(x -> interpBruchsContour.value(x) - interpEZContour.value(x)).average().getAsDouble(); int height = sharpOCT.getHeight();//make to use in lambda expression List<LinePoint> ezLine = IntStream.rangeClosed(minX, maxX) .mapToObj(x -> new LinePoint(x, height - interpEZContour.value(x) - avgDif)) .collect(Collectors.toList()); List<LinePoint> bmLine = IntStream.rangeClosed(minX, maxX) .mapToObj(x -> new LinePoint(x, height - interpBruchsContour.value(x))) .collect(Collectors.toList()); List<LinePoint> bmUnfiltLine = refinedBruchsMembraneContour.stream() .map((Point p) -> new LinePoint(p.x, height - p.getY())).collect(Collectors.toList()); Util.graphPoints(ezLine, bmLine, bmUnfiltLine); analysisManager.getImgPanel().setDrawnLines( IntStream.rangeClosed(minX, maxX).mapToObj(x -> new LinePoint(x, interpEZContour.value(x))) .collect(Collectors.toList()), IntStream.rangeClosed(minX, maxX).mapToObj(x -> new LinePoint(x, interpBruchsContour.value(x))) .collect(Collectors.toList())); /* Find the difference between the two contours (Bruch's membrane and the EZ + Bruch's membrane) and use this to determine where the edge of the EZ is */ List<LinePoint> diffLine = findDiffWithAdjustment(interpBruchsContour, 0D, interpEZContour, avgDif, minX, maxX); setProgress(90); // List<LinePoint> peaks = Util.findPeaksAndVallies(diffLine); // Util.graphPoints(diffLine, peaks); /* Find the first zero crossings of the difference line on both sides of the fovea. If a zero crossing can't be found then search for the first crossing of a value of 1, then 2, then 3, etc. until an X coordinate of a crossing is found on each side of the fovea. */ OptionalInt ezLeftEdge; double crossingThreshold = 0.25D; do { double filtThresh = crossingThreshold; System.out.println("Crossing threshold = " + crossingThreshold); ezLeftEdge = diffLine.stream().filter(lp -> lp.getY() <= filtThresh && lp.getX() < foveaCenterXPosition) .mapToInt(LinePoint::getX).max(); crossingThreshold += 0.25D; } while (!ezLeftEdge.isPresent()); OptionalInt ezRightEdge; crossingThreshold = 0.25D; do { double filtThresh = crossingThreshold; System.out.println("Crossing threshold = " + crossingThreshold); ezRightEdge = diffLine.stream() .filter(lp -> lp.getY() <= filtThresh && lp.getX() > foveaCenterXPosition) .mapToInt(LinePoint::getX).min(); crossingThreshold += 0.25D; } while (!ezRightEdge.isPresent()); //return findings return new EZEdgeCoord(ezLeftEdge.getAsInt(), ezRightEdge.getAsInt()); } @Override protected void process(List<Point> chunks) { if (debug) { analysisManager.getImgPanel().setDrawPoint(chunks.get(chunks.size() - 1)); } } @Override protected void done() { setProgress(100); //only add selections to screen if the EZ edge detection algorithm succeded try { //place selection showing each EZ edge EZEdgeCoord ez = get(); selMngr.addOrUpdateSelection(new OCTLine(ez.getLeftXCoord(), 0, analysisManager.getOct().getImageHeight(), SelectionType.NONFOVEAL, "EZ Left", true)); selMngr.addOrUpdateSelection(new OCTLine(ez.getRightXCoord(), 0, analysisManager.getOct().getImageHeight(), SelectionType.NONFOVEAL, "EZ Right", true)); //place selection at the center of the fovea int fv = analysisManager.getFoveaCenterXPosition(); OCTLine foveaSelection = new OCTLine(fv, 0, analysisManager.getOct().getImageHeight(), SelectionType.FOVEAL, "Fovea", false); selMngr.addOrUpdateSelection(foveaSelection); } catch (InterruptedException | ExecutionException ex) { Logger.getLogger(EZWorker.class.getName()).log(Level.SEVERE, "Automatic detection of EZ edges failed!", ex); JOptionPane.showMessageDialog(analysisManager.getImgPanel(), "Detection of the edges of the EZ can't be determined automatically by the application.\nYou will have to manually find the edges of the EZ.", "Can't Analyze Image", JOptionPane.ERROR_MESSAGE); } analysisManager.getImgPanel().repaint(); } /** * Determine if the supplied coordinate (excluding itself) in the supplied * black and white image is surrounded by white pixels on all sides. * * @param xStart * @param yStart * @param sharpOCT * @return */ public boolean isSurroundedByWhite(int xStart, int yStart, BufferedImage sharpOCT) { boolean allWhite = true; for (int x = -1; x < 2; x++) { for (int y = -1; y < 2; y++) { if (x != 0 && y != 0) { allWhite &= Util.calculateGrayScaleValue(sharpOCT.getRGB(xStart + x, yStart + y)) > 0; } } } return allWhite; } public boolean isContrastPoint(int x, int y, BufferedImage sharpOCT) { return Util.calculateGrayScaleValue(sharpOCT.getRGB(x, y)) == 0 && Util.calculateGrayScaleValue(sharpOCT.getRGB(x, y + 1)) > 0; } /** * Recursively search for a contour to the right of the supplied starting * point. If the contour returned contains the starting point then the * contour traced back to the start point rather than towards the edge of * the image. * * @param searchPoint point to search from * @param startPoint start search point * @param contourList list to add the contour points to * @param sharpOCT OCT to find the contour in * @return the next point in the contour after the search point */ public Point findContourRight(Point searchPoint, Cardinality searchDirection, Point startPoint, Cardinality startDirection, LinkedList<Point> contourList, BufferedImage sharpOCT, int depth) throws InterruptedException { if (debug) { publish(searchPoint); Thread.sleep(debug_sleep); } depth++; if (depth > depthThreshold) { //the recursive search has gone awry, we must terminate it before causing the stack to overflow return null; } Point nextPoint; Cardinality nextDirection; switch (searchDirection) { case SOUTH: if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x + 1, searchPoint.y)) > 0) { nextPoint = new Point(searchPoint); nextDirection = Cardinality.EAST; } else if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x + 1, searchPoint.y + 1)) == 0) { nextPoint = new Point(searchPoint.x + 1, searchPoint.y + 1); nextDirection = Cardinality.WEST; } else { nextPoint = new Point(searchPoint.x + 1, searchPoint.y); nextDirection = Cardinality.SOUTH; } break; case EAST: if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x, searchPoint.y - 1)) > 0) { nextPoint = new Point(searchPoint); nextDirection = Cardinality.NORTH; } else if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x + 1, searchPoint.y - 1)) == 0) { nextPoint = new Point(searchPoint.x + 1, searchPoint.y - 1); nextDirection = Cardinality.SOUTH; } else { nextPoint = new Point(searchPoint.x, searchPoint.y - 1); nextDirection = Cardinality.EAST; } break; case WEST: if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x, searchPoint.y + 1)) > 0) { nextPoint = new Point(searchPoint); nextDirection = Cardinality.SOUTH; } else if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x - 1, searchPoint.y + 1)) == 0) { nextPoint = new Point(searchPoint.x - 1, searchPoint.y + 1); nextDirection = Cardinality.NORTH; } else { nextPoint = new Point(searchPoint.x, searchPoint.y + 1); nextDirection = Cardinality.WEST; } break; case NORTH: if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x - 1, searchPoint.y)) > 0) { nextPoint = new Point(searchPoint); nextDirection = Cardinality.WEST; } else if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x - 1, searchPoint.y - 1)) == 0) { nextPoint = new Point(searchPoint.x - 1, searchPoint.y - 1); nextDirection = Cardinality.EAST; } else { nextPoint = new Point(searchPoint.x - 1, searchPoint.y); nextDirection = Cardinality.NORTH; } break; default: //will never happen, just placed in to make code compile nextPoint = new Point(searchPoint); nextDirection = Cardinality.EAST; break; } if (!((nextPoint.equals(startPoint) && nextDirection == startDirection) || nextPoint.y < 100 || nextPoint.y > sharpOCT.getHeight() - 20 || nextPoint.x <= 20 || nextPoint.x >= sharpOCT.getWidth() - 20)) { contourList.add(findContourRight(nextPoint, nextDirection, startPoint, startDirection, contourList, sharpOCT, depth)); } return nextPoint; } /** * Recursively search for a contour to the left of the supplied starting * point. If the contour returned contains the starting point then the * contour traced back to the start point rather than towards the edge of * the image. * * @param searchPoint point to search from * @param startPoint start search point * @param contourList list to add the contour points to * @param sharpOCT OCT to find the contour in * @return the next point in the contour after the search point */ public Point findContourLeft(Point searchPoint, Cardinality searchDirection, Point startPoint, Cardinality startDirection, LinkedList<Point> contourList, BufferedImage sharpOCT) throws InterruptedException { if (debug) { publish(searchPoint); Thread.sleep(debug_sleep); } Point nextPoint; Cardinality nextDirection; switch (searchDirection) { case SOUTH: if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x - 1, searchPoint.y)) > 0) { nextPoint = new Point(searchPoint); nextDirection = Cardinality.WEST; } else if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x - 1, searchPoint.y + 1)) == 0) { nextPoint = new Point(searchPoint.x - 1, searchPoint.y + 1); nextDirection = Cardinality.EAST; } else { nextPoint = new Point(searchPoint.x - 1, searchPoint.y); nextDirection = Cardinality.SOUTH; } break; case EAST: if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x, searchPoint.y + 1)) > 0) { nextPoint = new Point(searchPoint); nextDirection = Cardinality.SOUTH; } else if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x + 1, searchPoint.y + 1)) == 0) { nextPoint = new Point(searchPoint.x + 1, searchPoint.y + 1); nextDirection = Cardinality.NORTH; } else { nextPoint = new Point(searchPoint.x, searchPoint.y + 1); nextDirection = Cardinality.EAST; } break; case WEST: if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x, searchPoint.y - 1)) > 0) { nextPoint = new Point(searchPoint); nextDirection = Cardinality.NORTH; } else if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x - 1, searchPoint.y - 1)) == 0) { nextPoint = new Point(searchPoint.x - 1, searchPoint.y - 1); nextDirection = Cardinality.SOUTH; } else { nextPoint = new Point(searchPoint.x, searchPoint.y - 1); nextDirection = Cardinality.WEST; } break; case NORTH: if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x + 1, searchPoint.y)) > 0) { nextPoint = new Point(searchPoint); nextDirection = Cardinality.EAST; } else if (Util.calculateGrayScaleValue(sharpOCT.getRGB(searchPoint.x + 1, searchPoint.y - 1)) == 0) { nextPoint = new Point(searchPoint.x + 1, searchPoint.y - 1); nextDirection = Cardinality.WEST; } else { nextPoint = new Point(searchPoint.x + 1, searchPoint.y); nextDirection = Cardinality.NORTH; } break; default: //will never happen, just placed in to make code compile nextPoint = new Point(searchPoint); nextDirection = Cardinality.EAST; break; } if (!((nextPoint.equals(startPoint) && nextDirection == startDirection) || nextPoint.y < 100 || nextPoint.y > sharpOCT.getHeight() - 20 || nextPoint.x <= 20 || nextPoint.x >= sharpOCT.getWidth() - 20)) { contourList.add( findContourLeft(nextPoint, nextDirection, startPoint, startDirection, contourList, sharpOCT)); } return nextPoint; } public List<LinePoint> findDiffWithAdjustment(UnivariateFunction fa, double faYValueAdj, UnivariateFunction fb, double fbYValueAdj, int minX, int maxX) { return IntStream.rangeClosed(minX, maxX) .mapToObj(x -> new LinePoint(x, (fa.value(x) + faYValueAdj) - (fb.value(x) + fbYValueAdj))) .collect(Collectors.toList()); } }