java.lang.Object
- java.lang.Thread
- - gov.nih.mipav.model.algorithms.AlgorithmBase
  - - gov.nih.mipav.model.algorithms.registration.AlgorithmRegELSUNCOAR25D

All Implemented Interfaces:

java.awt.event.ActionListener, java.awt.event.WindowListener, java.lang.Runnable, java.util.EventListener
```
public class AlgorithmRegELSUNCOAR25D
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
  java.lang.Thread.State, java.lang.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 int`	`baseNumIter`	Limits number of iterations in ELSUNC, LEVENBERG_MARQUARDT, or NL2SOL optimization.
`private float[]`	`buffer`	DOCUMENT ME!
`private float[]`	`bufferA`	DOCUMENT ME!
`private float[]`	`bufferIW`	DOCUMENT ME!
`private float[]`	`bufferW`	DOCUMENT ME!
`private int`	`coarseNum`	Number of passes that will be made in the coarse sampling and fine sampling.
`private float`	`coarseRate`	Coarse and fine sampling parameters.
`private int`	`colorFactor`	1 for black and white, 4 for color.
`private int`	`costChoice`	Choice of which cost function to use.
`private boolean`	`doColor`	DOCUMENT ME!
`private int`	`DOF`	Maximum degrees of freedom when running the optimization.
`private boolean`	`doGraph`	Produce 2 output graphs - 1 for rotation and 1 for 2 translations.
`private boolean`	`doSubsample`	if true subsample.
`private int`	`fineNum`	Number of passes that will be made in the coarse sampling and fine sampling.
`private float`	`fineRate`	Coarse and fine sampling parameters.
`private 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 int`	`interp`	Interpolation method used in transformations.
`private 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 float`	`maxDim`	DOCUMENT ME!
`private int`	`maxIter`	Limits number of iterations in ELSUNC, LEVENBERG_MARQUARDT, or NL2SOL optimization.
`private 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 float`	`rotateBegin`	Coarse and fine sampling parameters.
`private float`	`rotateEnd`	Coarse and fine sampling parameters.
`private int`	`searchAlgorithm`
`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 boolean`	`transformVOIs`	if true transform VOIs.
`private boolean`	`useOutsideReferenceSlice`	DOCUMENT ME!
`private 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
`AlgorithmRegELSUNCOAR25D(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, int searchAlgorithm)`	Creates new automatic internal registration algorithm and sets necessary variables.
`AlgorithmRegELSUNCOAR25D(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, int searchAlgorithm)`	Creates new automatic internal registration algorithm and sets necessary variables.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`WildMagic.LibFoundation.Mathematics.Vector2f`	`calculateCenterOfMass2D(ModelSimpleImage image, ModelSimpleImage wgtImage, boolean isColor)`	Calculates the center of mass (gravity) of a 2D image.
`private 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 java.lang.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.
`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 java.util.Vector<MatrixListItem>[]`	`levelEight(ModelSimpleImage ref, ModelSimpleImage input)`	Takes two slices that have been subsampled by a factor of 8 or 16.
`private java.util.Vector<MatrixListItem>`	`levelFour(ModelSimpleImage ref, ModelSimpleImage input, java.util.Vector<MatrixListItem> minima, java.util.Vector<MatrixListItem> optMinima)`	Takes two slices that have been subsampled by a factor of four, and two vectors of minima.
`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 MatrixListItem`	`levelTwo(ModelSimpleImage ref, ModelSimpleImage input, java.util.Vector<MatrixListItem> minima)`	Takes two slices that have been subsampled by a factor of 2 and a vector of minima.
`void`	`runAlgorithm()`	Runs the image registration.
`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, join, join, join, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, start, stop, suspend, toString, yield

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Field Detail
  - 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 int coarseNum
```
    Number of passes that will be made in the coarse sampling and fine sampling.
  - fineNum
```
private int fineNum
```
    Number of passes that will be made in the coarse sampling and fine sampling.
  - colorFactor
```
private int colorFactor
```
    1 for black and white, 4 for color.
  - costChoice
```
private int costChoice
```
    Choice of which cost function to use.
  - doColor
```
private boolean doColor
```
    DOCUMENT ME!
  - DOF
```
private int DOF
```
    Maximum degrees of freedom when running the optimization.
  - doGraph
```
private 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 boolean doSubsample
```
    if true subsample.
  - searchAlgorithm
```
private int searchAlgorithm
```
  - ignoreCOG
```
private boolean ignoreCOG
```
    whether or not to use center of gravity for first translation.
  - 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 int interp
```
    Interpolation method used in transformations.
  - interp2
```
private 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 float maxDim
```
    DOCUMENT ME!
  - maxIter
```
private int maxIter
```
    Limits number of iterations in ELSUNC, LEVENBERG_MARQUARDT, or NL2SOL optimization. maxIter in the call to elsunc will be an integer multiple of baseNumIter
  - baseNumIter
```
private int baseNumIter
```
    Limits number of iterations in ELSUNC, LEVENBERG_MARQUARDT, or NL2SOL optimization. maxIter in the call to elsunc will be an integer multiple of baseNumIter
  - numMinima
```
private 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 float rotateBegin
```
    Coarse and fine sampling parameters.
  - rotateEnd
```
private float rotateEnd
```
    Coarse and fine sampling parameters.
  - coarseRate
```
private float coarseRate
```
    Coarse and fine sampling parameters.
  - fineRate
```
private 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 boolean transformVOIs
```
    if true transform VOIs.
  - useOutsideReferenceSlice
```
private boolean useOutsideReferenceSlice
```
    DOCUMENT ME!
  - weighted
```
private boolean weighted
```
    Flag to determine if there are weighted images or not.
  - weightSliceImage
```
private ModelImage weightSliceImage
```
    DOCUMENT ME!
- Constructor Detail
  - AlgorithmRegELSUNCOAR25D
```
public AlgorithmRegELSUNCOAR25D(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,
                                int searchAlgorithm)
```
    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 elsunc algorithm. maxIter in the call to elsunc will be an integer multiple of baseNumIter
    
    _numMinima - Number of minima from level 8 to test at level 4
    
    searchAlgorithm - ESLUNC, LEVENBERG_MARQUARDT, or NL2SOL.
  - AlgorithmRegELSUNCOAR25D
```
public AlgorithmRegELSUNCOAR25D(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,
                                int searchAlgorithm)
```
    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 elsunc algorithm. maxIter in the call to elsunc will be an integer multiple of baseNumIter
    
    _numMinima - Number of minima from level 8 to test at level 4
    
    searchAlgorithm - ESLUNC, LEVENBERG_MARQUARDT, or NL2SOL.
- Method Detail
  - calculateCenterOfMass2D
```
public 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
  - 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 void copyFloatData(ModelSimpleImage srcImage,
                           ModelSimpleImage resultImage)
```
    DOCUMENT ME!
    
    Parameters:
    
    srcImage - DOCUMENT ME!
    
    resultImage - DOCUMENT ME!
  - getConstructionInfo
```
private java.lang.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 AlgorithmELSUNC works in degrees) Scaling tolerance = n/(2R) Skewing tolerance = n/(2R)
  - 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.
  - levelEight
```
private java.util.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 java.util.Vector<MatrixListItem> levelFour(ModelSimpleImage ref,
                                                   ModelSimpleImage input,
                                                   java.util.Vector<MatrixListItem> minima,
                                                   java.util.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,
                                java.util.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.

Class AlgorithmRegELSUNCOAR25D

Nested Class Summary

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

Field Summary

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

Fields inherited from class java.lang.Thread

Constructor Summary

Method Summary

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

Methods inherited from class java.lang.Thread

Methods inherited from class java.lang.Object

Field Detail

allowLevel16

allowLevel2

allowLevel4

allowLevel8

answer

buffer

bufferA

bufferIW

bufferW

coarseNum

fineNum

colorFactor

costChoice

doColor

DOF

doGraph

doSubsample

searchAlgorithm

ignoreCOG

imageWeightIso

input1

input2

input3

inputImage

inputImage2

inputImage3

inputw_1

inputWeight

interp

interp2

iResols

isoImage

level1Factor

level2Factor

level4Factor

maxDim

maxIter

baseNumIter

numMinima

output_1

output_2

output_3

outsidePreReferenceSlice

outsideReferenceSlice

refImageNo

regToAdjImage

resample

resampleW

rigidFlag

rot

rotateBegin

rotateEnd

coarseRate

fineRate

simpleInput_1

simpleInputSub16_1

simpleInputSub2_1

simpleInputSub4_1

simpleInputSub8_1

simpleRef_1

simpleRefSub16_1

simpleRefSub2_1

simpleRefSub4_1

simpleRefSub8_1

simpleWeightI_1

simpleWeightISub16_1

simpleWeightISub2_1

simpleWeightISub4_1