Package gov.nih.mipav.model.algorithms

Class AlgorithmVOIProps.Calc34D

java.lang.Object

gov.nih.mipav.model.algorithms.AlgorithmVOIProps.Calc34D

All Implemented Interfaces:

java.lang.Runnable

Enclosing class:

AlgorithmVOIProps

private class AlgorithmVOIProps.Calc34D
extends java.lang.Object
implements java.lang.Runnable

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
private class	AlgorithmVOIProps.Calc34D.ContourStats	Stores the statistics for a single contour, color or grayscale.

Field Summary

Fields

Modifier and Type	Field	Description
private VOI	calcSelectedVOI	The VOI being used just for this calculation (may be a single curve of a single slice or entire VOI

Constructor Summary

Constructors

Constructor	Description
Calc34D(VOI selectedVOI)

Method Summary

Modifier and Type	Method	Description
private AlgorithmVOIProps.Calc34D.ContourStats	calcStatsPerContour(FileInfoBase fileInfo, VOIBase contour, int orientation, java.lang.String unit2DStr, java.lang.String unit3DStr, float ignoreMin, float ignoreMax, VOIStatisticalProperties statProperty, int iSlice, int iID)	Calculates statistics for a single contour.
private AlgorithmVOIProps.Calc34D.ContourStats	calcStatsPerContourRGB(FileInfoBase fileInfo, VOIBase contour, int orientation, java.lang.String unit2DStr, java.lang.String unit3DStr, float ignoreMinR, float ignoreMaxR, float ignoreMinG, float ignoreMaxG, float ignoreMinB, float ignoreMaxB, VOIStatisticalProperties statProperty, int iSlice, int iID)	Calculates statistics for a single contour.
private void	calcStatsTotal(VOI kVOI, VOIStatisticalProperties statProperty, FileInfoBase fileInfo, java.lang.String unit2DStr, java.lang.String unit3DStr, float ignoreMin, float ignoreMax)	Calculates the statistics for the VOI as a whole (across all contours within the VOI).
private void	calcStatsTotalRGB(VOI kVOI, VOIStatisticalProperties statProperty, FileInfoBase fileInfo, java.lang.String unit2DStr, java.lang.String unit3DStr, float ignoreMinR, float ignoreMaxR, float ignoreMinG, float ignoreMaxG, float ignoreMinB, float ignoreMaxB)
void	getMedianStatistics(AlgorithmVOIProps.Calc34D.ContourStats stats)	Calculates the median statistics for a grayscale image.
void	getMedianStatisticsRGB(AlgorithmVOIProps.Calc34D.ContourStats stats)	Calculates the median statistics for a color image.
void	getStdSkewStatistics(AlgorithmVOIProps.Calc34D.ContourStats stats, java.util.Vector<WildMagic.LibFoundation.Mathematics.Vector3f> kPositions, java.lang.String unit2DStr, java.lang.String unit3DStr, float ignoreMin, float ignoreMax)	Calculates the standard deviation, coefficient of skewness, coefficient of kurtosis and center of mass for a grayscale image.
void	getStdSkewStatisticsRGB(AlgorithmVOIProps.Calc34D.ContourStats stats, java.util.Vector<WildMagic.LibFoundation.Mathematics.Vector3f> kPositions, java.lang.String unit2DStr, java.lang.String unit3DStr, float ignoreMinR, float ignoreMaxR, float ignoreMinG, float ignoreMaxG, float ignoreMinB, float ignoreMaxB)	Calculates the standard deviation, coefficient of skewness, coefficient of kurtosis and center of mass for a color image.
private void	printTotals(AlgorithmVOIProps.Calc34D.ContourStats[] stats, VOIStatisticalProperties statProperty, java.lang.String unit2DStr, java.lang.String unit3DStr, java.lang.String end, float ignoreMin, float ignoreMax, double largestDistance)	Sums the statistics for a group of contours, where the statistics are first calculated per-contour.
private void	printTotals(java.util.Vector<AlgorithmVOIProps.Calc34D.ContourStats> allStats, VOIStatisticalProperties statProperty, java.lang.String unit2DStr, java.lang.String unit3DStr, java.lang.String end, float ignoreMin, float ignoreMax, double largestDistance)	Sums the statistics for a group of contours, where the statistics are first calculated per-contour.
private void	printTotalsRGB(AlgorithmVOIProps.Calc34D.ContourStats[] stats, VOIStatisticalProperties statProperty, java.lang.String unit2DStr, java.lang.String unit3DStr, java.lang.String end, float ignoreMinR, float ignoreMaxR, float ignoreMinG, float ignoreMaxG, float ignoreMinB, float ignoreMaxB, double largestDistance)	Sums the statistics for a group of contours, where the statistics are first calculated per-contour.
private void	printTotalsRGB(java.util.Vector<AlgorithmVOIProps.Calc34D.ContourStats> allStats, VOIStatisticalProperties statProperty, java.lang.String unit2DStr, java.lang.String unit3DStr, java.lang.String end, float ignoreMinR, float ignoreMaxR, float ignoreMinG, float ignoreMaxG, float ignoreMinB, float ignoreMaxB, double largestDistance)	Sums the statistics for a group of contours, where the statistics are first calculated per-contour.
void	run()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

calcSelectedVOI

private VOI calcSelectedVOI

The VOI being used just for this calculation (may be a single curve of a single slice or entire VOI

Constructor Detail

Calc34D

public Calc34D(VOI selectedVOI)

Method Detail

getMedianStatistics

public void getMedianStatistics(AlgorithmVOIProps.Calc34D.ContourStats stats)

Calculates the median statistics for a grayscale image. The image data is stored in the input stats.values. This function can be used for a single contour or a group of contours.

Parameters:

stats - contains the Vector of voxels inside the contour(s) used to calculate the median, mode and mode count.

getMedianStatisticsRGB

public void getMedianStatisticsRGB(AlgorithmVOIProps.Calc34D.ContourStats stats)

Calculates the median statistics for a color image. The image data is stored in the input stats.valuesRGB. This function can be used for a single contour or a group of contours.

Parameters:

stats - contains the Vector of voxels inside the contour(s) used to calculate the median, mode and mode count.

getStdSkewStatistics

public void getStdSkewStatistics(AlgorithmVOIProps.Calc34D.ContourStats stats,
                                 java.util.Vector<WildMagic.LibFoundation.Mathematics.Vector3f> kPositions,
                                 java.lang.String unit2DStr,
                                 java.lang.String unit3DStr,
                                 float ignoreMin,
                                 float ignoreMax)

Calculates the standard deviation, coefficient of skewness, coefficient of kurtosis and center of mass for a grayscale image.

Parameters:

stats - output values are written into stats.

kPositions - list of positions of voxels inside the contour (or multiple contours).

unit2DStr - , 2D label string

unit3DStr - , 3D label string

ignoreMin - , threshold minimum

ignoreMax - , threshold maximum

getStdSkewStatisticsRGB

public void getStdSkewStatisticsRGB(AlgorithmVOIProps.Calc34D.ContourStats stats,
                                    java.util.Vector<WildMagic.LibFoundation.Mathematics.Vector3f> kPositions,
                                    java.lang.String unit2DStr,
                                    java.lang.String unit3DStr,
                                    float ignoreMinR,
                                    float ignoreMaxR,
                                    float ignoreMinG,
                                    float ignoreMaxG,
                                    float ignoreMinB,
                                    float ignoreMaxB)

Calculates the standard deviation, coefficient of skewness, coefficient of kurtosis and center of mass for a color image.

Parameters:

stats - output values are written into stats.

kPositions - list of positions of voxels inside the contour (or multiple contours).

unit2DStr - , 2D label string

unit3DStr - , 3D label string

ignoreMinR - , threshold minimum red

ignoreMaxR - , threshold maximum red

ignoreMinG - , threshold minimum green

ignoreMaxG - , threshold maximum green

ignoreMinB - , threshold minimum blue

ignoreMaxB - , threshold maximum blue

run

public void run()

Specified by:

run in interface java.lang.Runnable

calcStatsPerContour

private AlgorithmVOIProps.Calc34D.ContourStats calcStatsPerContour(FileInfoBase fileInfo,
                                                                   VOIBase contour,
                                                                   int orientation,
                                                                   java.lang.String unit2DStr,
                                                                   java.lang.String unit3DStr,
                                                                   float ignoreMin,
                                                                   float ignoreMax,
                                                                   VOIStatisticalProperties statProperty,
                                                                   int iSlice,
                                                                   int iID)

Calculates statistics for a single contour. Calculations are done on an as-needed basis for faster performance.

Parameters:

fileInfo - information on image resolutions and dimensions

contour - input contour

orientation - the image plane the contour is on

unit2DStr - 2D label string

unit3DStr - 3D label string

ignoreMin - threshold minimum

ignoreMax - threshold maximum

statProperty - output labels are written to statProperty

iSlice - contour slice

iID - contour iD

Returns:

ContourStats data structure contains the statistic values.

calcStatsPerContourRGB

private AlgorithmVOIProps.Calc34D.ContourStats calcStatsPerContourRGB(FileInfoBase fileInfo,
                                                                      VOIBase contour,
                                                                      int orientation,
                                                                      java.lang.String unit2DStr,
                                                                      java.lang.String unit3DStr,
                                                                      float ignoreMinR,
                                                                      float ignoreMaxR,
                                                                      float ignoreMinG,
                                                                      float ignoreMaxG,
                                                                      float ignoreMinB,
                                                                      float ignoreMaxB,
                                                                      VOIStatisticalProperties statProperty,
                                                                      int iSlice,
                                                                      int iID)

Calculates statistics for a single contour. Calculations are done on an as-needed basis for faster performance.

Parameters:

fileInfo - information on image resolutions and dimensions

contour - input contour

orientation - the image plane the contour is on

unit2DStr - 2D label string

unit3DStr - 3D label string

ignoreMinR - threshold minimum red

ignoreMaxR - threshold maximum red

ignoreMinG - threshold minimum green

ignoreMaxG - threshold maximum green

ignoreMinB - threshold minimum blue

ignoreMaxB - threshold maximum blue

statProperty - output labels are written to statProperty

iSlice - contour slice

iID - contour iD

Returns:

ContourStats data structure contains the statistic values.

calcStatsTotal

private void calcStatsTotal(VOI kVOI,
                            VOIStatisticalProperties statProperty,
                            FileInfoBase fileInfo,
                            java.lang.String unit2DStr,
                            java.lang.String unit3DStr,
                            float ignoreMin,
                            float ignoreMax)

Calculates the statistics for the VOI as a whole (across all contours within the VOI). Calculations are done on an as-needed basis for faster performance.

Parameters:

contours - list of contours in the VOI

statProperty - stores the calculated output

fileInfo - information for image resolutions

unit2DStr - 2D label string

unit3DStr - 3D label string

ignoreMin - threshold minimum

ignoreMax - threshold maximum

largestDistance - largest Distance in the VOI. private void calcStatsTotal( Vector contours, VOIStatisticalProperties statProperty, FileInfoBase fileInfo, String unit2DStr, String unit3DStr, float ignoreMin, float ignoreMax, double largestDistance ) { ContourStats stats = new ContourStats(); // The following depend on each other: quantityDescription, volumeDescription, areaDescription, // circularityDescription, solidityDescription // If one is selected, all are calculated. if ( statsList[ indexOf( quantityDescription ) ] || statsList[ indexOf( volumeDescription ) ] || statsList[ indexOf( areaDescription ) ] || statsList[ indexOf( circularityDescription)] || statsList[ indexOf( solidityDescription)]) { stats.nVox = 0; stats.area = 0; stats.volume = 0; for ( int i = 0; i < contours.size(); i++ ) { int nVox = contours.elementAt(i).getNumVoxels(); stats.nVox += nVox; stats.area += nVox * (fileInfo.getResolutions()[0] * fileInfo.getResolutions()[1]); stats.volume += nVox * (fileInfo.getResolutions()[0] * fileInfo.getResolutions()[1] * fileInfo.getResolutions()[2]); } statProperty.setProperty(VOIStatisticList.areaDescription, nf.format(stats.area)); statProperty.setProperty(VOIStatisticList.volumeDescription, nf.format(stats.volume)); statProperty.setProperty(VOIStatisticList.quantityDescription, nf.format(stats.nVox)); } // If user selects perimeterDescription or circularityDescription: if ( statsList[ indexOf( perimeterDescription ) ] || statsList [ indexOf (circularityDescription) ]) { stats.perimeter = 0; for ( int i = 0; i < contours.size(); i++ ) { stats.perimeter += contours.elementAt(i).getLengthPtToPt(srcImage.getFileInfo(0).getResolutions()); } statProperty.setProperty(VOIStatisticList.perimeterDescription, nf.format(stats.perimeter)); } if ( statsList[indexOf(circularityDescription)]) { stats.circularity = (4.0 * Math.PI * stats.area)/(stats.perimeter * stats.perimeter); statProperty.setProperty(VOIStatisticList.circularityDescription + end, nf.format(stats.circularity)); } if ( statsList[indexOf(solidityDescription)]) { VOI convexKVOI = (VOI)kVOI.clone(); for ( int i = 0; i < convexKVOI.getCurves().size(); i++) { ((VOIContour)convexKVOI.getCurves().elementAt(i)).convexHull(); } ContourStats convexStats = new ContourStats(); BitSet convexMask = new BitSet( xDim * yDim * zDim ); convexKVOI.createBinaryMask3D(convexMask, xDim, yDim, false, false); if(rangeFlag != RangeType.NO_RANGE && rangeFlag != null) { //some intensity values need to be ignored in relevant calculations float fVal = 0.0f; for (int i = convexMask.nextSetBit(0); i >= 0; i = convexMask.nextSetBit(i+1)) { fVal = srcImage.getFloat(i); if (MipavUtil.inRange(ignoreMin, ignoreMax, fVal, rangeFlag)) { convexMask.set(i, false); } } } convexStats.nVox = convexMask.cardinality(); convexStats.area = convexStats.nVox * (fileInfo.getResolutions()[0] * fileInfo.getResolutions()[1]); stats.solidity = stats.area/convexStats.area; statProperty.setProperty(VOIStatisticList.solidityDescription, nf.format(stats.solidity)); } if (statsList[indexOf(numberOfIndentationsDescription)]) { stats.numberOfIndentations = contour.findVOIIndentations2D(srcImage, iSlice, null, false); statProperty.setProperty(VOIStatisticList.numberOfIndentationsDescription + end, nf.format(stats.numberOfIndentations)); } if (statsList[indexOf(meanCurvatureDescription)] || statsList[indexOf(stdDevCurvatureDescription)] || statsList[indexOf(meanNegativeCurvatureDescription)]) { Vector positions = new Vector(); Vector curvature = new Vector(); double meanCurvature[] = new double[1]; double stdDevCurvature[] = new double[1]; double meanNegativeCurvature[] = new double[1]; boolean smooth = true; VOIBase convexContour = new VOIContour((VOIContour)contour); convexContour.findPositionAndCurvature( srcImage, positions, curvature, smooth, meanCurvature, stdDevCurvature, meanNegativeCurvature); if (statsList[indexOf(meanCurvatureDescription)]) { stats.meanCurvature = meanCurvature[0]; statProperty.setProperty(VOIStatisticList.meanCurvatureDescription + end, nf.format(stats.meanCurvature)); } if (statsList[indexOf(stdDevCurvatureDescription)]) { stats.stdDevCurvature = stdDevCurvature[0]; statProperty.setProperty(VOIStatisticList.stdDevCurvatureDescription + end, nf.format(stats.stdDevCurvature)); } if (statsList[indexOf(meanNegativeCurvatureDescription)]) { stats.meanNegativeCurvature = meanNegativeCurvature[0]; statProperty.setProperty(VOIStatisticList.meanNegativeCurvatureDescription + end, nf.format(stats.meanNegativeCurvature)); } } // The following statistics are derived from the minIntensity, maxIntensity, avgIntensity, and sumIntensity: // median, mode, modeCount // deviationDescription, skewnessDescription, kurtosisDescription, massCenterDescription if ( statsList[ indexOf( minIntensity ) ] || statsList[ indexOf( maxIntensity ) ] || statsList[ indexOf( avgIntensity ) ] || statsList[ indexOf( sumIntensities ) ] || statsList[ indexOf( median ) ] || statsList[ indexOf( mode ) ] || statsList[ indexOf( modeCount ) ] || statsList[ indexOf( deviationDescription ) ] || statsList[ indexOf( skewnessDescription ) ] || statsList[ indexOf( kurtosisDescription ) ] || statsList[ indexOf( massCenterDescription ) ] ) { stats.nVox = 0; stats.values = new Vector(); stats.valuesRGB = new Vector(); for ( int i = 0; i < contours.size(); i++ ) { int nVox = contours.elementAt(i).getNumVoxels(); stats.nVox += nVox; if (srcImage.isColorImage()) { ColorRGB kMin = new ColorRGB(); ColorRGB kMax = new ColorRGB(); ColorRGB kSum = new ColorRGB(); stats.valuesRGB.addAll( contours.elementAt(i).calcRGBIntensity( srcImage, kMin, kMax, kSum, ignoreMin, ignoreMax, rangeFlag ) ); if ( i == 0 ) { stats.minIntenRed = kMin.R; stats.minIntenGreen = kMin.G; stats.minIntenBlue = kMin.B; stats.maxIntenRed = kMax.R; stats.maxIntenGreen = kMax.G; stats.maxIntenBlue = kMax.B; } stats.minIntenRed = Math.min( stats.minIntenRed, kMin.R ); stats.minIntenGreen = Math.min( stats.minIntenGreen, kMin.G ); stats.minIntenBlue = Math.min( stats.minIntenBlue, kMin.B ); stats.maxIntenRed = Math.max( stats.minIntenRed, kMax.R ); stats.maxIntenGreen = Math.max( stats.minIntenGreen, kMax.G ); stats.maxIntenBlue = Math.max( stats.minIntenBlue, kMax.B ); stats.sumR += kSum.R; stats.sumG += kSum.G; stats.sumB += kSum.B; } else { Vector3f kMinMax = new Vector3f(); stats.values.addAll( contours.elementAt(i).calcIntensity( srcImage, kMinMax, ignoreMin, ignoreMax, rangeFlag ) ); if ( i == 0 ) { stats.minIntensity = kMinMax.X; stats.maxIntensity = kMinMax.Y; } stats.minIntensity = Math.min( stats.minIntensity, kMinMax.X ); stats.maxIntensity = Math.max( stats.maxIntensity, kMinMax.Y ); stats.sum += kMinMax.Z; } } statProperty.setProperty(VOIStatisticList.quantityDescription, nf.format(stats.nVox)); if (srcImage.isColorImage()) { stats.avgIntenR = stats.sumR/stats.nVox; stats.avgIntenG = stats.sumG/stats.nVox; stats.avgIntenB = stats.sumB/stats.nVox; statProperty.setProperty(VOIStatisticList.minIntensity + "Red", nf.format(stats.minIntenRed)); statProperty.setProperty(VOIStatisticList.maxIntensity + "Red", nf.format(stats.maxIntenRed)); statProperty.setProperty(VOIStatisticList.minIntensity + "Green", nf.format(stats.minIntenGreen)); statProperty.setProperty(VOIStatisticList.maxIntensity + "Green", nf.format(stats.maxIntenGreen)); statProperty.setProperty(VOIStatisticList.minIntensity + "Blue", nf.format(stats.minIntenBlue)); statProperty.setProperty(VOIStatisticList.maxIntensity + "Blue", nf.format(stats.maxIntenBlue)); statProperty.setProperty(VOIStatisticList.avgIntensity + "Red", nf.format(stats.avgIntenR)); statProperty.setProperty(VOIStatisticList.avgIntensity + "Green", nf.format(stats.avgIntenG)); statProperty.setProperty(VOIStatisticList.avgIntensity + "Blue", nf.format(stats.avgIntenB)); statProperty.setProperty(VOIStatisticList.sumIntensities + "Red", nf.format(stats.sumR)); statProperty.setProperty(VOIStatisticList.sumIntensities + "Green", nf.format(stats.sumG)); statProperty.setProperty(VOIStatisticList.sumIntensities + "Blue", nf.format(stats.sumB)); } else { stats.avgInten = stats.sum/stats.nVox; statProperty.setProperty(VOIStatisticList.minIntensity, nf.format(stats.minIntensity)); statProperty.setProperty(VOIStatisticList.maxIntensity, nf.format(stats.maxIntensity)); statProperty.setProperty(VOIStatisticList.avgIntensity, nf.format(stats.avgInten)); statProperty.setProperty(VOIStatisticList.sumIntensities, nf.format(stats.sum)); } // median, mode, modeCount if ( statsList[ indexOf( median ) ] || statsList[ indexOf( mode ) ] || statsList[ indexOf( modeCount ) ] ) { if (srcImage.isColorImage()) { getMedianStatisticsRGB( stats ); statProperty.setProperty(VOIStatisticList.mode + "Red", nf.format(stats.modeR)); statProperty.setProperty(VOIStatisticList.mode + "Green", nf.format(stats.modeG)); statProperty.setProperty(VOIStatisticList.mode + "Blue", nf.format(stats.modeB)); statProperty.setProperty(VOIStatisticList.modeCount + "Red", nf.format(stats.maxCountR)); statProperty.setProperty(VOIStatisticList.modeCount + "Green", nf.format(stats.maxCountG)); statProperty.setProperty(VOIStatisticList.modeCount + "Blue", nf.format(stats.maxCountB)); statProperty.setProperty(VOIStatisticList.median + "Red", nf.format(stats.medianR)); statProperty.setProperty(VOIStatisticList.median + "Green", nf.format(stats.medianG)); statProperty.setProperty(VOIStatisticList.median + "Blue", nf.format(stats.medianB)); } else { getMedianStatistics( stats ); statProperty.setProperty(VOIStatisticList.mode, nf.format(stats.mode)); statProperty.setProperty(VOIStatisticList.modeCount, nf.format(stats.maxCount)); statProperty.setProperty(VOIStatisticList.median, nf.format(stats.median)); } } // deviationDescription, skewnessDescription, kurtosisDescription, massCenterDescription if ( statsList[ indexOf( deviationDescription ) ] || statsList[ indexOf( skewnessDescription ) ] || statsList[ indexOf( kurtosisDescription ) ] || statsList[ indexOf( massCenterDescription ) ] ) { Vector kPositions = new Vector(); for ( int i = 0; i < contours.size(); i++ ) { kPositions.addAll( contours.elementAt(i).getMaskPositions() ); } if (srcImage.isColorImage()) { getStdSkewStatisticsRGB(stats, kPositions, unit2DStr, unit3DStr, ignoreMin, ignoreMax); statProperty.setProperty(VOIStatisticList.deviationDescription + "Red", nf.format(stats.stdDevR)); statProperty.setProperty(VOIStatisticList.deviationDescription + "Green", nf.format(stats.stdDevG)); statProperty.setProperty(VOIStatisticList.deviationDescription + "Blue", nf.format(stats.stdDevB)); statProperty.setProperty(VOIStatisticList.skewnessDescription + "Red", nf.format(stats.skewnessR)); statProperty.setProperty(VOIStatisticList.skewnessDescription + "Green", nf.format(stats.skewnessG)); statProperty.setProperty(VOIStatisticList.skewnessDescription + "Blue", nf.format(stats.skewnessB)); statProperty.setProperty(VOIStatisticList.kurtosisDescription + "Red", nf.format(stats.kurtosisR)); statProperty.setProperty(VOIStatisticList.kurtosisDescription + "Green", nf.format(stats.kurtosisG)); statProperty.setProperty(VOIStatisticList.kurtosisDescription + "Blue", nf.format(stats.kurtosisB)); statProperty.setProperty(VOIStatisticList.massCenterDescription + "Red", stats.massCenterDescriptionR); statProperty.setProperty(VOIStatisticList.massCenterDescription + "Green", stats.massCenterDescriptionG); statProperty.setProperty(VOIStatisticList.massCenterDescription + "Blue", stats.massCenterDescriptionB); } else { getStdSkewStatistics(stats, kPositions, unit2DStr, unit3DStr, ignoreMin, ignoreMax); statProperty.setProperty(VOIStatisticList.deviationDescription, nf.format(stats.stdDev)); statProperty.setProperty(VOIStatisticList.skewnessDescription, nf.format(stats.skewness)); statProperty.setProperty(VOIStatisticList.kurtosisDescription , nf.format(stats.kurtosis)); statProperty.setProperty(VOIStatisticList.massCenterDescription, stats.massCenterDescription); } } } // If user selects geometricCenterDescription if ( statsList[ indexOf( geometricCenterDescription ) ] ) { Vector3f selectedCOM = calcSelectedVOI.getGeometricCenter(); selectedCOM.X *= srcImage.getFileInfo(0).getResolutions()[0]; selectedCOM.Y *= srcImage.getFileInfo(0).getResolutions()[1]; String unitStr = unit2DStr + "\tZ"; if (srcImage.getNDims() > 2) { selectedCOM.Z *= srcImage.getFileInfo(0).getResolutions()[2]; unitStr = unit3DStr; } String comStr = unitStr + "\n\t\t" + nf.format(selectedCOM.X) + "\t" + nf.format(selectedCOM.Y) + "\t" + nf.format(selectedCOM.Z); comStr = addScannerLabels(comStr, selectedCOM); stats.gCenterString = new String(comStr); statProperty.setProperty(VOIStatisticList.geometricCenterDescription, stats.gCenterString); } // If user selects largestSliceDistanceDescription: if ( statsList[ indexOf( largestSliceDistanceDescription ) ] ) { for ( int i = 0; i < contours.size(); i++ ) { Vector3f kPos1 = new Vector3f(); Vector3f kPos2 = new Vector3f(); if ( i == 0 ) { stats.largestContourDistance = ((VOIContour) (contours.elementAt(i))).calcLargestSliceDistance( fileInfo.getResolutions()[0], fileInfo.getResolutions()[1], kPos1, kPos2); // Uncomment the following to at the VOILine to the image: //VOILine kLine = new VOILine(); //kLine.add(kPos1); //kLine.add(kPos2); //VOI kVOI = new VOI( (short)srcImage.getVOIs().size(), "LargestDist", VOI.LINE, 0 ); //kVOI.importCurve(kLine); //srcImage.registerVOI(kVOI); } else { stats.largestContourDistance = Math.max( stats.largestContourDistance, ((VOIContour) (contours.elementAt(i))).calcLargestSliceDistance( fileInfo.getResolutions()[0], fileInfo.getResolutions()[1], kPos1, kPos2)); // Uncomment the following to at the VOILine to the image: //VOILine kLine = new VOILine(); //kLine.add(kPos1); //kLine.add(kPos2); //VOI kVOI = new VOI( (short)srcImage.getVOIs().size(), "LargestDist", VOI.LINE, 0 ); //kVOI.importCurve(kLine); //srcImage.registerVOI(kVOI); } } statProperty.setProperty(VOIStatisticList.largestSliceDistanceDescription, nf.format(stats.largestContourDistance)); } if ( statsList[ indexOf( largestDistanceDescription ) ] ) { stats.largestContourDistance = largestDistance; statProperty.setProperty(VOIStatisticList.largestDistanceDescription, nf.format(stats.largestContourDistance)); } // Ellipsoid fit parameters are calculated as a group, if one is selected, calculate all. // For the VOI, only calculate these parameters for one contour: if ( statsList[ indexOf( axisDescription ) ] || statsList[ indexOf( eccentricityDescription ) ] || statsList[ indexOf( majorAxisDescription ) ] || statsList[ indexOf( minorAxisDescription ) ] ) { float[] tmpPAxis = new float[1]; float[] tmpEcc = new float[1]; float[] tmpMajorAxis = new float[1]; float[] tmpMinorAxis = new float[1]; ((VOIContour)contours.firstElement()).secondOrderAttributes(srcImage, tmpPAxis, tmpEcc, tmpMajorAxis, tmpMinorAxis); stats.PAxis = tmpPAxis[0]; stats.Ecc = tmpEcc[0]; stats.MajorAxis = tmpMajorAxis[0]; stats.MinorAxis = tmpMinorAxis[0]; System.out.println("HERE2"); statProperty.setProperty(VOIStatisticList.axisDescription, nf.format(stats.PAxis)); statProperty.setProperty(VOIStatisticList.eccentricityDescription, nf.format(stats.Ecc)); statProperty.setProperty(VOIStatisticList.majorAxisDescription, nf.format(stats.MajorAxis)); statProperty.setProperty(VOIStatisticList.minorAxisDescription, nf.format(stats.MinorAxis)); } }

calcStatsTotalRGB

private void calcStatsTotalRGB(VOI kVOI,
                               VOIStatisticalProperties statProperty,
                               FileInfoBase fileInfo,
                               java.lang.String unit2DStr,
                               java.lang.String unit3DStr,
                               float ignoreMinR,
                               float ignoreMaxR,
                               float ignoreMinG,
                               float ignoreMaxG,
                               float ignoreMinB,
                               float ignoreMaxB)

printTotals

private void printTotals(AlgorithmVOIProps.Calc34D.ContourStats[] stats,
                         VOIStatisticalProperties statProperty,
                         java.lang.String unit2DStr,
                         java.lang.String unit3DStr,
                         java.lang.String end,
                         float ignoreMin,
                         float ignoreMax,
                         double largestDistance)

Sums the statistics for a group of contours, where the statistics are first calculated per-contour.

Parameters:

stats - array of per-contour statistics

statProperty - output is written to the statProperty

unit2DStr - 2D label string

unit3DStr - 3D label string

end - tag for statProperty labels

ignoreMin - threshold minimum

ignoreMax - threshold maximum

largestDistance - VOI largest distance.

printTotalsRGB

private void printTotalsRGB(AlgorithmVOIProps.Calc34D.ContourStats[] stats,
                            VOIStatisticalProperties statProperty,
                            java.lang.String unit2DStr,
                            java.lang.String unit3DStr,
                            java.lang.String end,
                            float ignoreMinR,
                            float ignoreMaxR,
                            float ignoreMinG,
                            float ignoreMaxG,
                            float ignoreMinB,
                            float ignoreMaxB,
                            double largestDistance)

Sums the statistics for a group of contours, where the statistics are first calculated per-contour.

Parameters:

stats - array of per-contour statistics

statProperty - output is written to the statProperty

unit2DStr - 2D label string

unit3DStr - 3D label string

end - tag for statProperty labels

ignoreMinR - threshold minimum red

ignoreMaxR - threshold maximum red

ignoreMinG - threshold minimum green

ignoreMaxG - threshold maximum green

ignoreMinB - threshold minimum blue

ignoreMaxB - threshold maximum blue

largestDistance - VOI largest distance.

printTotals

private void printTotals(java.util.Vector<AlgorithmVOIProps.Calc34D.ContourStats> allStats,
                         VOIStatisticalProperties statProperty,
                         java.lang.String unit2DStr,
                         java.lang.String unit3DStr,
                         java.lang.String end,
                         float ignoreMin,
                         float ignoreMax,
                         double largestDistance)

Sums the statistics for a group of contours, where the statistics are first calculated per-contour.

Parameters:

allStats - list of per-contour statistics

statProperty - output is written to the statProperty

unit2DStr - 2D label string

unit3DStr - 3D label string

end - tag for statProperty labels

ignoreMin - threshold minimum

ignoreMax - threshold maximum

largestDistance - VOI largest distance.

printTotalsRGB

private void printTotalsRGB(java.util.Vector<AlgorithmVOIProps.Calc34D.ContourStats> allStats,
                            VOIStatisticalProperties statProperty,
                            java.lang.String unit2DStr,
                            java.lang.String unit3DStr,
                            java.lang.String end,
                            float ignoreMinR,
                            float ignoreMaxR,
                            float ignoreMinG,
                            float ignoreMaxG,
                            float ignoreMinB,
                            float ignoreMaxB,
                            double largestDistance)

Sums the statistics for a group of contours, where the statistics are first calculated per-contour.

Parameters:

allStats - list of per-contour statistics

statProperty - output is written to the statProperty

unit2DStr - 2D label string

unit3DStr - 3D label string

end - tag for statProperty labels

ignoreMinR - threshold minimum red

ignoreMaxR - threshold maximum red

ignoreMinG - threshold minimum green

ignoreMaxG - threshold maximum green

ignoreMinB - threshold minimum blue

ignoreMaxB - threshold maximum blue

largestDistance - VOI largest distance.