Package gov.nih.mipav.model.algorithms.registration

Class AlgorithmRegOAR25D2

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.registration.AlgorithmRegOAR25D2

All Implemented Interfaces:

ActionListener, WindowListener, Runnable, EventListener

public class AlgorithmRegOAR25D2
extends AlgorithmBase

This is an automatic registration method based on FLIRT. FLIRT stands for FMRIB's Linear Image Registration Tool. For more information on FLIRT, visit their homepage at http://www.fmrib.ox.ac.uk/fsl/flirt/. Their main paper is:

Jenkinson, M. and Smith, S. (2001a).
A global optimisation method for robust affine registration of brain images.
Medical Image Analysis, 5(2):143-156.

Internal registration is performed within one 3D image.

In adjacent mode the first slice above the reference slice is registered to the reference slice, then the second slice above the reference slice is registered to the first slice above the reference slice, and so on until the last slice is registered the next to last slice. Then, the first slice below the reference slice is registered to the reference slice, the second slice below the reference slice is registered to first slice below the reference slice, and so on until the first slice is registered to the second slice. In reference mode every slice is simply registered to the reference slice.

Our algorithm works as follows:
1.) We find the minimum resolution of the images.
2.) We transform the images into isotropic voxels.
3.) We subsample the images by 2, 4, and 8 or 16, depending on the resolution.
We loop thru a number of iterations equal to the number of slices - 1 in adjacent mode or equal to the number of slices in reference mode with one slice as the input slice and one slice as the reference slice. For each iteration: 4.) With the slices that were subsampled by 8 or 16, we call levelEight. This function will use the coarse sampling rate and optimize translations and global scale at the given rotation. So for example, if the coarse sampling range were -30 to 30 at every 15 degrees, we would optimize at rotations of -30, -15, 0, 15, 30.
5.) Still in levelEight, we now measure the cost at the fine sampling rate. We interpolate the translations and global scale to come up with a good guess as to what the optimized translation would be at that point.
6.) We take the top 20% of the points and optimize them.
7.) We now have a large multi-array of costs. 20% of those have been optimized and placed back into their original position in the multi-array. We look at the 3 neighbors of a point: +, =, or - one fine sample. If our point has a cost greater than any of these, it is not a minima. Otherwise it is. We save it in a vector of minima.
8.) We optimize the minima over rotation as well as translations and global scale. (Previously we had not optimized over rotation.) We return two vectors, one containing the minima before optimization, one containing the minima after optimization.
9.) We now call levelFour with the slices subsampled by 4 and the vectors of minima. We measure the costs of the minima on the new slices and sort them. We take the top numMinima in each vector (pre-optimization and post-optimization) and optimize them. We put them all into one vector.
10.) We perturb the rotation by zero and by plus-minus fineDelta. If it's not a rigid transformation, we then perturb the global scaling by factors of 0.8, 0.9, 1.0, 1.1, and 1.2.
11.) We optimize the perturbations. We return a vector of the perturbed, optimized minima.
12.) We now call levelTwo with the slices subsampled by 2. We measure the costs of the minima at the new slices. We optimize the best minimum with 4 degrees of freedom, then 5, then 6. If the user has limited the degrees of freedom to 3, there will only be one optimization run, with 3 degrees of freedom. The function returns the best minimum after optimization.
13.) We call levelOne with the un-subsampled slices. At levelOne, one optimization run is performed, with the maximum allowable degrees of freedom, as specified by the user (the max is 6).
14.) The best answer is returned from levelOne. The inverse of the matrix from this answer is used to register the input slice to the reference slice. The registered input slice data is imported into inputImage.

Note that when 6 degrees of freedom is used the rotation is set equal to 0 because diffX sets (0,2), diffY sets (1,2), scaleX sets (0,0), scaleY sets (1,1), skewX sets (0,1), and skewY sets (1,0) so all 6 elements are set.

Author:

Matthew McAuliffe, Neva Cherniavsky, Benjamin Link - Added code to use less memory. (April 2003)

Nested Class Summary

Nested classes/interfaces inherited from class java.lang.Thread

Thread.Builder, Thread.State, Thread.UncaughtExceptionHandler

Field Summary

Fields

Modifier and Type	Field	Description
private boolean	allowLevel16	DOCUMENT ME!
private boolean	allowLevel2	Flags are true if weighted image is not present or if weighted image subsampling occurred, false if weighted image subsampling did not occur.
private boolean	allowLevel4	DOCUMENT ME!
private boolean	allowLevel8	DOCUMENT ME!
private MatrixListItem	answer	Final answer after registration.
private final int	baseNumIter	Limits number of iterations in Powell optimization. maxIter in the call to Powell's will be an integer multiple of baseNumIter
private float[]	buffer	DOCUMENT ME!
private float[]	bufferA	DOCUMENT ME!
private float[]	bufferIW	DOCUMENT ME!
private float[]	bufferW	DOCUMENT ME!
private final int	coarseNum	Number of passes that will be made in the coarse sampling and fine sampling.
private final float	coarseRate	Coarse and fine sampling parameters.
private final int	colorFactor	1 for black and white, 4 for color.
private final int	costChoice	Choice of which cost function to use.
private final boolean	doColor	DOCUMENT ME!
private final int	DOF	Maximum degrees of freedom when running the optimization.
private final boolean	doGraph	Produce 2 output graphs - 1 for rotation and 1 for 2 translations.
private final boolean	doSubsample	if true subsample.
private final int	fineNum
private final float	fineRate	Coarse and fine sampling parameters.
private final boolean	ignoreCOG	whether or not to use center of gravity for first translation.
private ModelImage	imageWeightIso	DOCUMENT ME!
private ModelImage	input1	Image used to import a slice from inputImage.
private ModelImage	input2	Image used to import a slice from inputImage2.
private ModelImage	input3	Image used to import a slice from inputImage3.
private ModelImage	inputImage	This is the image in which internal registration will be performed.
private ModelImage	inputImage2	Other images which will not determine the registration, but which will undergo the same transformations as input image.
private ModelImage	inputImage3	DOCUMENT ME!
private ModelImage	inputw_1	Image used to import a slice from inputWeight.
private ModelImage	inputWeight	This gives weights for the input image - higher weights mean a greater impact in that area on the registration.
private final int	interp	Interpolation method used in transformations.
private final int	interp2	Interpolation method used in output.
private float[]	iResols	The voxel resolutions of the input image.
private ModelImage	isoImage	new to this version: must keep isoImage around if image needed to be transformed.
private float	level1Factor	Multiplication factor for level 1 - will be set based on subsampling.
private float	level2Factor	Multiplication factor for level 2 - will be set based on subsampling.
private float	level4Factor	Multiplication factor for level 4 - will be set based on subsampling.
private final float	maxDim	DOCUMENT ME!
private final int	numMinima	Number of minima from level 8 to test at level 4.
private ModelImage	output_1	DOCUMENT ME!
private ModelImage	output_2	DOCUMENT ME!
private ModelImage	output_3	DOCUMENT ME!
private ModelImage	outsidePreReferenceSlice	DOCUMENT ME!
private ModelImage	outsideReferenceSlice	DOCUMENT ME!
private int	refImageNo	Indicates the first slice used as a reference slice, if regToAdjImage is true.
private boolean	regToAdjImage	If true use adjacent image for registration.
private boolean	resample	true if resolutions unequal, false if resolutions equal.
private boolean	resampleW	true if weight image must be resampled.
private boolean	rigidFlag	Flag used to indicate if the registration is ridgid (rotation and translation - DOF = 3.
private float[]	rot	Arrays used for producing graphs for DOF == 3 and register to reference image.
private final float	rotateBegin	Coarse and fine sampling parameters.
private final float	rotateEnd	Coarse and fine sampling parameters.
private ModelSimpleImage	simpleInput_1	Simple version of an image slice of the input image.
private ModelSimpleImage	simpleInputSub16_1	Simple version of an image slice of the input image, subsampled by 16.
private ModelSimpleImage	simpleInputSub2_1	Simple version of an image slice of the input image, subsampled by 2.
private ModelSimpleImage	simpleInputSub4_1	Simple version of an image slice of the input image, subsampled by 4.
private ModelSimpleImage	simpleInputSub8_1	Simple version of an image slice of the input image, subsampled by 8.
private ModelSimpleImage	simpleRef_1	Simple version of input image.
private ModelSimpleImage	simpleRefSub16_1	Simple version of input image, subsampled by 16.
private ModelSimpleImage	simpleRefSub2_1	Simple version of input image, subsampled by 2.
private ModelSimpleImage	simpleRefSub4_1	Simple version of input image, subsampled by 4.
private ModelSimpleImage	simpleRefSub8_1	Simple version of input image, subsampled by 8.
private ModelSimpleImage	simpleWeightI_1	DOCUMENT ME!
private ModelSimpleImage	simpleWeightISub16_1	DOCUMENT ME!
private ModelSimpleImage	simpleWeightISub2_1	DOCUMENT ME!
private ModelSimpleImage	simpleWeightISub4_1	DOCUMENT ME!
private ModelSimpleImage	simpleWeightISub8_1	DOCUMENT ME!
private ModelSimpleImage	simpleWeightR_1	Simple version of weighted input image.
private ModelSimpleImage	simpleWeightRSub16_1	Simple version of weighted input image, subsampled by 16.
private ModelSimpleImage	simpleWeightRSub2_1	Simple version of weighted input image, subsampled by 2.
private ModelSimpleImage	simpleWeightRSub4_1	Simple version of weighted input image, subsampled by 4.
private ModelSimpleImage	simpleWeightRSub8_1	Simple version of weighted input image, subsampled by 8.
private double[]	sliceCosts	DOCUMENT ME!
private float[][]	trans	DOCUMENT ME!
private final boolean	transformVOIs	if true transform VOIs.
private boolean	useOutsideReferenceSlice	DOCUMENT ME!
private final boolean	weighted	Flag to determine if there are weighted images or not.
private ModelImage	weightSliceImage	DOCUMENT ME!

Fields inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

destFlag, destImage, image25D, mask, maxProgressValue, minProgressValue, multiThreadingEnabled, nthreads, progress, progressModulus, progressStep, runningInSeparateThread, separable, srcImage, threadStopped

Fields inherited from class java.lang.Thread

MAX_PRIORITY, MIN_PRIORITY, NORM_PRIORITY

Constructor Summary

Constructors

Constructor	Description
AlgorithmRegOAR25D2(ModelImage _image, int _costChoice, int _DOF, int _interp, int _interp2, boolean mode, int refImageNum, float _rotateBegin, float _rotateEnd, float _coarseRate, float _fineRate, boolean doGraph, boolean doSubsample, boolean transformVOIs, int _baseNumIter, int _numMinima)	Creates new automatic internal registration algorithm and sets necessary variables.
AlgorithmRegOAR25D2(ModelImage _image, ModelImage _inputWeight, int _costChoice, int _DOF, int _interp, int _interp2, boolean mode, int refImageNum, float _rotateBegin, float _rotateEnd, float _coarseRate, float _fineRate, boolean doGraph, boolean doSubsample, boolean transformVOIs, int _baseNumIter, int _numMinima)	Creates new automatic internal registration algorithm and sets necessary variables.

Method Summary

Modifier and Type	Method	Description
static WildMagic.LibFoundation.Mathematics.Vector2f	calculateCenterOfMass2D(ModelSimpleImage image, ModelSimpleImage wgtImage, boolean isColor)	Calculates the center of mass (gravity) of a 2D image.
private static void	copyFloatData(ModelSimpleImage srcImage, ModelSimpleImage resultImage)	DOCUMENT ME!
void	disposeLocal()	Dispose of local variables that may be taking up lots of room.
void	finalize()	Prepares this class for destruction.
private String	getConstructionInfo()	Creates a string with the parameters that the image was constructed with.
double[]	getCosts()	accessor for costs.
float[]	getRot()	accessor for rot.
private double[]	getTolerance(int DOF)	Gets the tolerance vector based on the degrees of freedom (the length of the tolerance is the degrees of freedom) and.
private static double[]	getTolerance(int DOF, boolean rigidFlag, float maxDim)
float[][]	getTrans()	accessor for trans.
ModelImage	getTransformedImage()	accessor to get the internally registered image.
private void	interpolate(double x, double[] initial, double[][] tranforms, boolean scale)	Performs a bilinear interpolation on points.
private static void	interpolate(double x, double[] initial, double[][] tranforms, boolean scale, int coarseNum)
private Vector<MatrixListItem>[]	levelEight(ModelSimpleImage ref, ModelSimpleImage input)	Takes two slices that have been subsampled by a factor of 8 or 16.
private static Vector<MatrixListItem>[]	levelEightMultiThread(ModelSimpleImage ref, ModelSimpleImage input, int DOF, boolean rigidFlag, float maxDim, int baseNumIter, float rotateBegin, float rotateEnd, float coarseRate, float fineRate, int coarseNum, int fineNum, int costChoice, boolean doColor, boolean ignoreCOG, boolean weighted, boolean allowLevel16, ModelSimpleImage simpleWeightRSub16_1, ModelSimpleImage simpleWeightRSub8_1, ModelSimpleImage simpleWeightISub16_1, ModelSimpleImage simpleWeightISub8_1)
private Vector<MatrixListItem>	levelFour(ModelSimpleImage ref, ModelSimpleImage input, Vector<MatrixListItem> minima, Vector<MatrixListItem> optMinima)	Takes two slices that have been subsampled by a factor of four, and two vectors of minima.
private static Vector<MatrixListItem>	levelFourMultiThread(ModelSimpleImage ref, ModelSimpleImage input, Vector<MatrixListItem> minima, Vector<MatrixListItem> optMinima, int numMinima, int DOF, boolean rigidFlag, float maxDim, int baseNumIter, float rotateBegin, float rotateEnd, float coarseRate, float fineRate, int coarseNum, int fineNum, int costChoice, boolean doColor, boolean ignoreCOG, boolean weighted, float level4Factor, ModelSimpleImage simpleWeightRSub4_1, ModelSimpleImage simpleWeightISub4_1)
private MatrixListItem	levelOne(ModelSimpleImage ref, ModelSimpleImage input, MatrixListItem item, int frame)	Takes the two slices, no subsampling, and the best minimum so far.
private MatrixListItem	levelOne2D(ModelSimpleImage ref, ModelSimpleImage input)	This routine is used only with DOF = 2, translations only.
private static MatrixListItem	levelOne2DMultiThread(ModelSimpleImage ref, ModelSimpleImage input, int frame, int DOF, boolean rigidFlag, float maxDim, int baseNumIter, float rotateBegin, float rotateEnd, float coarseRate, float fineRate, int coarseNum, int fineNum, int costChoice, boolean doColor, boolean ignoreCOG, boolean weighted, float level1Factor, ModelSimpleImage simpleWeightR_1, ModelSimpleImage simpleWeightI_1, double[] sliceCosts)
private static MatrixListItem	levelOneMultiThread(ModelSimpleImage ref, ModelSimpleImage input, MatrixListItem item, int frame, int DOF, boolean rigidFlag, float maxDim, int baseNumIter, float rotateBegin, float rotateEnd, float coarseRate, float fineRate, int coarseNum, int fineNum, int costChoice, boolean doColor, boolean ignoreCOG, boolean weighted, float level1Factor, ModelSimpleImage simpleWeightR_1, ModelSimpleImage simpleWeightI_1, double[] sliceCosts)
private MatrixListItem	levelTwo(ModelSimpleImage ref, ModelSimpleImage input, Vector<MatrixListItem> minima)	Takes two slices that have been subsampled by a factor of 2 and a vector of minima.
private static MatrixListItem	levelTwoMultiThread(ModelSimpleImage ref, ModelSimpleImage input, Vector<MatrixListItem> minima, int numMinima, int DOF, boolean rigidFlag, float maxDim, int baseNumIter, float rotateBegin, float rotateEnd, float coarseRate, float fineRate, int coarseNum, int fineNum, int costChoice, boolean doColor, boolean ignoreCOG, boolean weighted, float level2Factor, ModelSimpleImage simpleWeightRSub2_1, ModelSimpleImage simpleWeightISub2_1)
private void	registerSlice(int rNumber, int startIndex, int endIndex, int sliceSize, int[] iExtents)
void	runAlgorithm()	Runs the image registration.
void	runAlgorithmTest()
void	setInputImage2(ModelImage inputImage2)	inputImage2 is not used to determine the registration, but each slice of inputImage2 undergoes the same transformation as inputImage.
void	setInputImage3(ModelImage inputImage3)	inputImage3 is not used to determine the registration, but each slice of inputImage3 undergoes the same transformation as inputImage.
boolean	setReferenceSlice(ModelImage refSlice)	allows the user to pass in an OUTSIDE reference slice.
private static ModelSimpleImage	subSample2DimBy2(ModelSimpleImage srcImage, ModelSimpleImage resultImage, boolean isColor)	DOCUMENT ME!

Methods inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, generateProgressValues, getDestImage, getElapsedTime, getMask, getMaxProgressValue, getMinProgressValue, getNumberOfThreads, getProgress, getProgressChangeListener, getProgressChangeListeners, getProgressModulus, getProgressStep, getProgressValues, getSrcImage, isCompleted, isImage25D, isMultiThreadingEnabled, isRunningInSeparateThread, isThreadStopped, linkProgressToAlgorithm, linkProgressToAlgorithm, makeProgress, notifyListeners, removeListener, removeProgressChangeListener, run, setCompleted, setImage25D, setMask, setMaxProgressValue, setMinProgressValue, setMultiThreadingEnabled, setNumberOfThreads, setProgress, setProgressModulus, setProgressStep, setProgressValues, setProgressValues, setRunningInSeparateThread, setSrcImage, setStartTime, setThreadStopped, startMethod, windowActivated, windowClosed, windowClosing, windowDeactivated, windowDeiconified, windowIconified, windowOpened

Methods inherited from class java.lang.Thread

activeCount, checkAccess, clone, countStackFrames, currentThread, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, isVirtual, join, join, join, join, ofPlatform, ofVirtual, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, sleep, start, startVirtualThread, stop, suspend, threadId, toString, yield

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Details

allowLevel16

private boolean allowLevel16

DOCUMENT ME!

allowLevel2

private boolean allowLevel2

Flags are true if weighted image is not present or if weighted image subsampling occurred, false if weighted image subsampling did not occur.

allowLevel4

private boolean allowLevel4

DOCUMENT ME!

allowLevel8

private boolean allowLevel8

DOCUMENT ME!

answer

private MatrixListItem answer

Final answer after registration.

buffer

private float[] buffer

DOCUMENT ME!

bufferA

private float[] bufferA

DOCUMENT ME!

bufferIW

private float[] bufferIW

DOCUMENT ME!

bufferW

private float[] bufferW

DOCUMENT ME!

coarseNum

private final int coarseNum

Number of passes that will be made in the coarse sampling and fine sampling.

fineNum

private final int fineNum

colorFactor

private final int colorFactor

1 for black and white, 4 for color.

costChoice

private final int costChoice

Choice of which cost function to use.

doColor

private final boolean doColor

DOCUMENT ME!

DOF

private final int DOF

Maximum degrees of freedom when running the optimization.

doGraph

private final boolean doGraph

Produce 2 output graphs - 1 for rotation and 1 for 2 translations. Only can be used for DOF == 3 and register to reference slice

doSubsample

private final boolean doSubsample

if true subsample.

ignoreCOG

private final boolean ignoreCOG

whether or not to use center of gravity for first translation.

See Also:

• Constant Field Values

imageWeightIso

private ModelImage imageWeightIso

DOCUMENT ME!

input1

private ModelImage input1

Image used to import a slice from inputImage.

input2

private ModelImage input2

Image used to import a slice from inputImage2.

input3

private ModelImage input3

Image used to import a slice from inputImage3.

inputImage

private ModelImage inputImage

This is the image in which internal registration will be performed.

inputImage2

private ModelImage inputImage2

Other images which will not determine the registration, but which will undergo the same transformations as input image. Useful if registering a color image based on only 1 of the colors

inputImage3

private ModelImage inputImage3

DOCUMENT ME!

inputw_1

private ModelImage inputw_1

Image used to import a slice from inputWeight.

inputWeight

private ModelImage inputWeight

This gives weights for the input image - higher weights mean a greater impact in that area on the registration.

interp

private final int interp

Interpolation method used in transformations.

interp2

private final int interp2

Interpolation method used in output.

iResols

private float[] iResols

The voxel resolutions of the input image.

isoImage

private ModelImage isoImage

new to this version: must keep isoImage around if image needed to be transformed.

level1Factor

private float level1Factor

Multiplication factor for level 1 - will be set based on subsampling.

level2Factor

private float level2Factor

Multiplication factor for level 2 - will be set based on subsampling.

level4Factor

private float level4Factor

Multiplication factor for level 4 - will be set based on subsampling.

maxDim

private final float maxDim

DOCUMENT ME!

baseNumIter

private final int baseNumIter

Limits number of iterations in Powell optimization. maxIter in the call to Powell's will be an integer multiple of baseNumIter

numMinima

private final int numMinima

Number of minima from level 8 to test at level 4.

output_1

private ModelImage output_1

DOCUMENT ME!

output_2

private ModelImage output_2

DOCUMENT ME!

output_3

private ModelImage output_3

DOCUMENT ME!

outsidePreReferenceSlice

private ModelImage outsidePreReferenceSlice

DOCUMENT ME!

outsideReferenceSlice

private ModelImage outsideReferenceSlice

DOCUMENT ME!

refImageNo

private int refImageNo

Indicates the first slice used as a reference slice, if regToAdjImage is true.

regToAdjImage

private boolean regToAdjImage

If true use adjacent image for registration. If false use image slice reference number to indicate the image slice to register all images to.

resample

private boolean resample

true if resolutions unequal, false if resolutions equal.

resampleW

private boolean resampleW

true if weight image must be resampled.

rigidFlag

private boolean rigidFlag

Flag used to indicate if the registration is ridgid (rotation and translation - DOF = 3.

rot

private float[] rot

Arrays used for producing graphs for DOF == 3 and register to reference image.

rotateBegin

private final float rotateBegin

Coarse and fine sampling parameters.

rotateEnd

private final float rotateEnd

Coarse and fine sampling parameters.

coarseRate

private final float coarseRate

Coarse and fine sampling parameters.

fineRate

private final float fineRate

Coarse and fine sampling parameters.

simpleInput_1

private ModelSimpleImage simpleInput_1

Simple version of an image slice of the input image.

simpleInputSub16_1

private ModelSimpleImage simpleInputSub16_1

Simple version of an image slice of the input image, subsampled by 16.

simpleInputSub2_1

private ModelSimpleImage simpleInputSub2_1

Simple version of an image slice of the input image, subsampled by 2.

simpleInputSub4_1

private ModelSimpleImage simpleInputSub4_1

Simple version of an image slice of the input image, subsampled by 4.

simpleInputSub8_1

private ModelSimpleImage simpleInputSub8_1

Simple version of an image slice of the input image, subsampled by 8.

simpleRef_1

private ModelSimpleImage simpleRef_1

Simple version of input image.

simpleRefSub16_1

private ModelSimpleImage simpleRefSub16_1

Simple version of input image, subsampled by 16.

simpleRefSub2_1

private ModelSimpleImage simpleRefSub2_1

Simple version of input image, subsampled by 2.

simpleRefSub4_1

private ModelSimpleImage simpleRefSub4_1

Simple version of input image, subsampled by 4.

simpleRefSub8_1

private ModelSimpleImage simpleRefSub8_1

Simple version of input image, subsampled by 8.

simpleWeightI_1

private ModelSimpleImage simpleWeightI_1

DOCUMENT ME!

simpleWeightISub16_1

private ModelSimpleImage simpleWeightISub16_1

DOCUMENT ME!

simpleWeightISub2_1

private ModelSimpleImage simpleWeightISub2_1

DOCUMENT ME!

simpleWeightISub4_1

private ModelSimpleImage simpleWeightISub4_1

DOCUMENT ME!

simpleWeightISub8_1

private ModelSimpleImage simpleWeightISub8_1

DOCUMENT ME!

simpleWeightR_1

private ModelSimpleImage simpleWeightR_1

Simple version of weighted input image.

simpleWeightRSub16_1

private ModelSimpleImage simpleWeightRSub16_1

Simple version of weighted input image, subsampled by 16.

simpleWeightRSub2_1

private ModelSimpleImage simpleWeightRSub2_1

Simple version of weighted input image, subsampled by 2.

simpleWeightRSub4_1

private ModelSimpleImage simpleWeightRSub4_1

Simple version of weighted input image, subsampled by 4.

simpleWeightRSub8_1

private ModelSimpleImage simpleWeightRSub8_1

Simple version of weighted input image, subsampled by 8.

sliceCosts

private double[] sliceCosts

DOCUMENT ME!

trans

private float[][] trans

DOCUMENT ME!

transformVOIs

private final boolean transformVOIs

if true transform VOIs.

useOutsideReferenceSlice

private boolean useOutsideReferenceSlice

DOCUMENT ME!

weighted

private final boolean weighted

Flag to determine if there are weighted images or not.

weightSliceImage

private ModelImage weightSliceImage

DOCUMENT ME!

Constructor Details

AlgorithmRegOAR25D2

public AlgorithmRegOAR25D2(ModelImage _image,
 int _costChoice,
 int _DOF,
 int _interp,
 int _interp2,
 boolean mode,
 int refImageNum,
 float _rotateBegin,
 float _rotateEnd,
 float _coarseRate,
 float _fineRate,
 boolean doGraph,
 boolean doSubsample,
 boolean transformVOIs,
 int _baseNumIter,
 int _numMinima)

Creates new automatic internal registration algorithm and sets necessary variables.

Parameters:

_image - Input image

_costChoice - Choice of cost functions, like correlation ratio or mutual information.

_DOF - Degrees of freedom for registration

_interp - Interpolation method used in transformations.

_interp2 - Interpolation method used in output

mode - If true, register to adjacent. If false, register to reference.

refImageNum - If register to reference, the slice all other slices are registered to. If register to adjacent, the first slice used as a reference.

_rotateBegin - Beginning of coarse sampling range (i.e., -60 degrees).

_rotateEnd - End of coarse sampling range (i.e., 60 degrees).

_coarseRate - Point at which coarse samples should be taken (i.e., every 45 degrees).

_fineRate - Point at which fine samples should be taken (i.e., every 15 degrees).

doGraph - If true produce 2 output graphs - one for rotation and one for 2 translations

doSubsample - If true subsample

transformVOIs - If true, transform VOIs

_baseNumIter - Limits the number of iterations of Powell's algorithm. maxIter in the call to Powell's will be an integer multiple of baseNumIter

_numMinima - Number of minima from level 8 to test at level 4

AlgorithmRegOAR25D2

public AlgorithmRegOAR25D2(ModelImage _image,
 ModelImage _inputWeight,
 int _costChoice,
 int _DOF,
 int _interp,
 int _interp2,
 boolean mode,
 int refImageNum,
 float _rotateBegin,
 float _rotateEnd,
 float _coarseRate,
 float _fineRate,
 boolean doGraph,
 boolean doSubsample,
 boolean transformVOIs,
 int _baseNumIter,
 int _numMinima)

Creates new automatic internal registration algorithm and sets necessary variables.

Parameters:

_image - Input image

_inputWeight - Input weighted image, used to give certain areas of the image greater impact on the registration.

_costChoice - Choice of cost functions, like correlation ratio or mutual information.

_DOF - DOCUMENT ME!

_interp - Interpolation method used in transformations.

_interp2 - Interpolation method used in output

mode - If true, register to adjacent. If false, register to reference.

refImageNum - If register to reference, the slice all other slices are registered to. If register to adjacent, the first slice used as a reference.

_rotateBegin - Beginning of coarse sampling range (i.e., -60 degrees).

_rotateEnd - End of coarse sampling range (i.e., 60 degrees).

_coarseRate - Point at which coarse samples should be taken (i.e., every 45 degrees).

_fineRate - Point at which fine samples should be taken (i.e., every 15 degrees).

doGraph - If true produce 2 output graphs - 1 for rotation and one for 2 translations

doSubsample - If true subsample

transformVOIs - If true, transform VOIs

_baseNumIter - Limits the number of iterations of Powell's algorithm. maxIter in the call to Powell's will be an integer multiple of baseNumIter

_numMinima - Number of minima from level 8 to test at level 4

Method Details

calculateCenterOfMass2D

public static WildMagic.LibFoundation.Mathematics.Vector2f calculateCenterOfMass2D(ModelSimpleImage image,
 ModelSimpleImage wgtImage,
 boolean isColor)

Calculates the center of mass (gravity) of a 2D image. In image space where the upper left hand corner of the image is 0,0. The x axis goes left to right, y axis goes top to bottom. (i.e. the right hand rule). One could simply multiply by voxel resolutions.

Parameters:

image - DOCUMENT ME!

wgtImage - DOCUMENT ME!

isColor - DOCUMENT ME!

Returns:

the center of mass as a 2D point

disposeLocal

public void disposeLocal()

Dispose of local variables that may be taking up lots of room.

finalize

public void finalize()

Prepares this class for destruction.

Overrides:

finalize in class AlgorithmBase

getCosts

public double[] getCosts()

accessor for costs.

Returns:

double[] costs

getRot

public float[] getRot()

accessor for rot.

Returns:

rot

getTrans

public float[][] getTrans()

accessor for trans.

Returns:

trans

getTransformedImage

public ModelImage getTransformedImage()

accessor to get the internally registered image.

Returns:

inputImage

runAlgorithm

public void runAlgorithm()

Runs the image registration. If the resolutions are unequal, the image is transformed into isotropic pixels. The resolutions of the two images after the xy isotropic transformation will be the same in the x and y dimensions. That resolution will equal the minimum resolution. If the image is weighted, the weight image is transformed into isotropic pixels in the same manner as the original. Then the image is subsampled by 2, 4, and 8 or 16. If the image is too small it will not be subsampled down to the smallest level; if it is too big, it will be subsampled to 16. The same is done with the weight image if necessary. The program loops thru levelEight, levelFour, levelTwo, and levelOne with one slice as the reference slice and one slice as the input slice. The function levelEight is called with the slices subsampled by 8 or 16; it returns two vectors with minima. Then the function levelFour is called with slices subsampled by 4 and the two vectors; it returns one vector of minima. The function levelTwo is called with slices subsampled by 2 and the vector; it returns an "answer" in the form of a MatrixListItem, which is a convenient way of storing the point, the matrix, and the cost of the minimum. Then the function levelOne is called with the minimum; it returns a final "answer", or minimum, which is used to register the input slice to the reference slice. The registered input slice data is imported into inputImage.

Specified by:

runAlgorithm in class AlgorithmBase

runAlgorithmTest

public void runAlgorithmTest()

registerSlice

private void registerSlice(int rNumber,
 int startIndex,
 int endIndex,
 int sliceSize,
 int[] iExtents)

setInputImage2

public void setInputImage2(ModelImage inputImage2)

inputImage2 is not used to determine the registration, but each slice of inputImage2 undergoes the same transformation as inputImage. This is useful for color images where you wish the registration to be determined by only 1 of the colors

Parameters:

inputImage2 - DOCUMENT ME!

setInputImage3

public void setInputImage3(ModelImage inputImage3)

inputImage3 is not used to determine the registration, but each slice of inputImage3 undergoes the same transformation as inputImage. This is useful for color images where you wish the registration to be determined by only 1 of the colors

Parameters:

inputImage3 - DOCUMENT ME!

setReferenceSlice

public boolean setReferenceSlice(ModelImage refSlice)

allows the user to pass in an OUTSIDE reference slice.

Parameters:

refSlice - 2-Dim image for reference

Returns:

DOCUMENT ME!

subSample2DimBy2

private static ModelSimpleImage subSample2DimBy2(ModelSimpleImage srcImage,
 ModelSimpleImage resultImage,
 boolean isColor)

DOCUMENT ME!

Parameters:

srcImage - DOCUMENT ME!

resultImage - DOCUMENT ME!

isColor - DOCUMENT ME!

Returns:

DOCUMENT ME!

copyFloatData

private static void copyFloatData(ModelSimpleImage srcImage,
 ModelSimpleImage resultImage)

DOCUMENT ME!

Parameters:

srcImage - DOCUMENT ME!

resultImage - DOCUMENT ME!

getConstructionInfo

private String getConstructionInfo()

Creates a string with the parameters that the image was constructed with.

Returns:

Construction info.

getTolerance

private double[] getTolerance(int DOF)

Gets the tolerance vector based on the degrees of freedom (the length of the tolerance is the degrees of freedom) and.

Parameters:

DOF - Degrees of freedom, will be length of vector.

Returns:

New tolerance vector to send to optimization.

Based on FLIRT paper: let n=pixel dimension (in one dimension) R=brain radius, here assumed to be half of field-of-view Translation tolerance = n/2 Rotation tolerance = (180/PI)*n/(2R) (converted to degrees because AlgorithmPowell works in degrees) Scaling tolerance = n/(2R) Skewing tolerance = n/(2R)

getTolerance

private static double[] getTolerance(int DOF,
 boolean rigidFlag,
 float maxDim)

interpolate

private void interpolate(double x,
 double[] initial,
 double[][] tranforms,
 boolean scale)

Performs a bilinear interpolation on points. Takes an initial point, a vector of values to set, and an array in which to look at neighbors of that point. Sets the appropriate values in the vector. Does not set scale if the scale parameter is false.

Parameters:

x - Initial index into array.

initial - Vector to set; if scale is true, set two translations and a scale. Otherwise just set translations.

tranforms - DOCUMENT ME!

scale - true means set the scale in the vector.

interpolate

private static void interpolate(double x,
 double[] initial,
 double[][] tranforms,
 boolean scale,
 int coarseNum)

levelEight

private Vector<MatrixListItem>[] levelEight(ModelSimpleImage ref,
 ModelSimpleImage input)

Takes two slices that have been subsampled by a factor of 8 or 16. Sets up the cost function with the slices and the weighted slices, if necessary. Uses the coarse sampling rate and optimize translations and global scale at the given rotation. So for example, if the coarse sampling range were -30 to 30 at every 15 degrees, we would optimize at rotations of -30, -15, 0, 15, 30. Measures the cost at the fine sampling rate. Interpolates the translations and global scale to come up with a good guess as to what the optimized translation would be at that point. Takes the top 20% of the points and optimizes them. Now have a large multi-array of costs. 20% of those have been optimized and placed back into their original position in the multi-array. Looks at the 3 neighbors of a point: +, =, or - one fine sample. If the point has a cost greater than any of these, it is not a minima. Otherwise it is. Saves it in a vector of minima. Optimizes the minima over rotation as well as translations and global scale. (Previously had not optimized over rotation.) Returns two vectors, one containing the minima before optimization, one containing the minima after optimization.

Parameters:

ref - Subsampled by 8 or 16 reference slice.

input - Subsampled by 8 or 16 input slice.

Returns:

List of preoptimized and optimized points.

levelFour

private Vector<MatrixListItem> levelFour(ModelSimpleImage ref,
 ModelSimpleImage input,
 Vector<MatrixListItem> minima,
 Vector<MatrixListItem> optMinima)

Takes two slices that have been subsampled by a factor of four, and two vectors of minima. Sets up the cost function with the slices and the weighted slices, if necessary. Adds the level4Factor determined during subsampling. Measures the costs of the minima on the images and sort them. Takes the top three in each vector (pre-optimization and post-optimization) and optimizes them. Puts them all into one vector. Perturbs the rotation by zero and by plus-minus fineDelta. If it's not a rigid transformation, perturbs the scales by 0, plus-minus .1, then plus-minus .2. Optimize the perturbations. Returns a vector of the perturbed, optimized minima.

Parameters:

ref - Reference slice, subsampled by 4.

input - Input slice, subsampled by 4.

minima - Preoptimized minima.

optMinima - DOCUMENT ME!

Returns:

A vector of perturbed, optimized minima.

levelOne

private MatrixListItem levelOne(ModelSimpleImage ref,
 ModelSimpleImage input,
 MatrixListItem item,
 int frame)

Takes the two slices, no subsampling, and the best minimum so far. Sets up the cost function with the slices and the weighted slices, if necessary. Adds the level1Factor determined during subsampling. Performs one optimization run, with the maximum allowable degrees of freedom as specified by the user (the max is 7). Returns the best minimum.

Parameters:

ref - Reference slice.

input - Input slice.

item - Best minimum so far.

frame - DOCUMENT ME!

Returns:

Best minimum after optimization.

levelOne2D

private MatrixListItem levelOne2D(ModelSimpleImage ref,
 ModelSimpleImage input)

This routine is used only with DOF = 2, translations only. LevelEight, levelFour, and levelTwo are skipped Takes the two slices, no subsampling. Sets up the cost function with the slices and the weighted slices. Adds the level1Factor determined during subsampling. Performs one optimization run, with 2 degrees of freedom

Parameters:

ref - Reference slice.

input - Input slice.

Returns:

Best minimum after optimization.

levelTwo

private MatrixListItem levelTwo(ModelSimpleImage ref,
 ModelSimpleImage input,
 Vector<MatrixListItem> minima)

Takes two slices that have been subsampled by a factor of 2 and a vector of minima. Sets up the cost function with the images and the weighted images, if necessary. Adds the level2Factor determined during subsampling. Measures the costs of the minima at the images. Optimizes the best minimum with 4 degrees of freedom, then 5, then 7. If the user has limited the degrees of freedom to 3, there will only be one optimization run, with 3 degrees of freedom. Returns the best minimum after optimization.

Parameters:

ref - Reference slice, subsampled by 2.

input - Input slice, subsampled by 2.

minima - Minima.

Returns:

The optimized minimum.

levelEightMultiThread

private static Vector<MatrixListItem>[] levelEightMultiThread(ModelSimpleImage ref,
 ModelSimpleImage input,
 int DOF,
 boolean rigidFlag,
 float maxDim,
 int baseNumIter,
 float rotateBegin,
 float rotateEnd,
 float coarseRate,
 float fineRate,
 int coarseNum,
 int fineNum,
 int costChoice,
 boolean doColor,
 boolean ignoreCOG,
 boolean weighted,
 boolean allowLevel16,
 ModelSimpleImage simpleWeightRSub16_1,
 ModelSimpleImage simpleWeightRSub8_1,
 ModelSimpleImage simpleWeightISub16_1,
 ModelSimpleImage simpleWeightISub8_1)

levelFourMultiThread

private static Vector<MatrixListItem> levelFourMultiThread(ModelSimpleImage ref,
 ModelSimpleImage input,
 Vector<MatrixListItem> minima,
 Vector<MatrixListItem> optMinima,
 int numMinima,
 int DOF,
 boolean rigidFlag,
 float maxDim,
 int baseNumIter,
 float rotateBegin,
 float rotateEnd,
 float coarseRate,
 float fineRate,
 int coarseNum,
 int fineNum,
 int costChoice,
 boolean doColor,
 boolean ignoreCOG,
 boolean weighted,
 float level4Factor,
 ModelSimpleImage simpleWeightRSub4_1,
 ModelSimpleImage simpleWeightISub4_1)

levelTwoMultiThread

private static MatrixListItem levelTwoMultiThread(ModelSimpleImage ref,
 ModelSimpleImage input,
 Vector<MatrixListItem> minima,
 int numMinima,
 int DOF,
 boolean rigidFlag,
 float maxDim,
 int baseNumIter,
 float rotateBegin,
 float rotateEnd,
 float coarseRate,
 float fineRate,
 int coarseNum,
 int fineNum,
 int costChoice,
 boolean doColor,
 boolean ignoreCOG,
 boolean weighted,
 float level2Factor,
 ModelSimpleImage simpleWeightRSub2_1,
 ModelSimpleImage simpleWeightISub2_1)

levelOneMultiThread

private static MatrixListItem levelOneMultiThread(ModelSimpleImage ref,
 ModelSimpleImage input,
 MatrixListItem item,
 int frame,
 int DOF,
 boolean rigidFlag,
 float maxDim,
 int baseNumIter,
 float rotateBegin,
 float rotateEnd,
 float coarseRate,
 float fineRate,
 int coarseNum,
 int fineNum,
 int costChoice,
 boolean doColor,
 boolean ignoreCOG,
 boolean weighted,
 float level1Factor,
 ModelSimpleImage simpleWeightR_1,
 ModelSimpleImage simpleWeightI_1,
 double[] sliceCosts)

levelOne2DMultiThread

private static MatrixListItem levelOne2DMultiThread(ModelSimpleImage ref,
 ModelSimpleImage input,
 int frame,
 int DOF,
 boolean rigidFlag,
 float maxDim,
 int baseNumIter,
 float rotateBegin,
 float rotateEnd,
 float coarseRate,
 float fineRate,
 int coarseNum,
 int fineNum,
 int costChoice,
 boolean doColor,
 boolean ignoreCOG,
 boolean weighted,
 float level1Factor,
 ModelSimpleImage simpleWeightR_1,
 ModelSimpleImage simpleWeightI_1,
 double[] sliceCosts)