Package gov.nih.mipav.model.algorithms.DiffusionTensorImaging

Class AlgorithmDWI2DTI

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.DiffusionTensorImaging.AlgorithmDWI2DTI

All Implemented Interfaces:

AlgorithmInterface, ActionListener, WindowListener, Runnable, EventListener

public class AlgorithmDWI2DTI
extends AlgorithmBase
implements AlgorithmInterface

Algorithm calculates a Diffusion Tensor Image from a series of Diffusion Weighted Images. See: Introduction to Diffusion Tensor Imaging, by Susumu Mori

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 AlgorithmBrainSurfaceExtractor	alg	handle to BSE Algorithm *
private final HashMap<String,float[]>	m_3dbufferMap_float
private final HashMap<String,int[]>	m_3dbufferMap_int
private final HashMap<String,float[]>	m_4dbufferMap_float
private final HashMap<String,int[]>	m_4dbufferMap_int
private String[][]	m_aakDWIList	List of file names for the Diffusion Weighted Images, from the .path file.
private int[]	m_aiMatrixEntries	keeps track of unique entries in the BMatrix
private boolean	m_bDisplayB0	Whether to just display the B0 weighted image and return, or to do a full calculation:
private boolean	m_bUseDTIParameters	When true, use the ModelImage DTI parameters.
private float	m_fMeanNoise	The mean noise value:
private final int	m_iBOrig	Number of different entries in the BMatrix:
private final int	m_iDimX	X Dimension of the input images:
private final int	m_iDimY	Y Dimension of the input images:
private final int	m_iSlices	Number of slices in the input images:
private final int	m_iWeights	Number of images in the weighted series:
private ViewJFrameImage	m_kB0Frame	ViewJFrameImage for displaying the B0 weighted image:
private ModelImage	m_kB0Image	B0 weighted image:
private WildMagic.LibFoundation.Mathematics.GMatrixd	m_kBMatrix	General matrix storing BMatrix values.
private ModelImage	m_kDTI	Output DTI Image:
private ModelImage	m_kDWIImage	DWI Image 4D series of weighted diffusion images
private ModelImage	m_kMaskImage	Mask Image for masking brain regions during tensor calculation:
private String	m_kRawImageFormat	Format of the raw data: (float, int, dicom, etc.)

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
AlgorithmDWI2DTI(ModelImage kMaskImage, boolean bDisplayB0, int iSlices, int iDimX, int iDimY, int iBOrig, int iWeights, float fMeanNoise, String[][] aakDWIList, int[] aiMatrixEntries, WildMagic.LibFoundation.Mathematics.GMatrixd kBMatrix, String kRawFormat)	Create a new AlgorithmDWI2DTI
AlgorithmDWI2DTI(ModelImage kDWIImage, ModelImage maskImage)

Method Summary

Modifier and Type	Method	Description
void	algorithmPerformed(AlgorithmBase algorithm)	Called after an algorithm this listener is registered to exits (maybe successfully, maybe not).
void	calculateDTI(int start, int end, float[] dtiData, float[][][] weightData, Jama.Matrix B, Jama.Matrix H)
void	calculateDTIVoxel(float[] dtiData, float[][] dwiData, float[][][] weightData, int x, int y, int z, Jama.Matrix B)
void	calculateDTIVoxel2(float[] dtiData, float[][] dwiData, float[][][] weightData, int x, int y, int z, Jama.Matrix H, int volumeSize)
Jama.Matrix	calculateMatrix(Jama.Matrix m)
private void	createDWI()
float[]	createDWIImage()	Second step in processing the diffusion weighted images.
private void	createMaskImage()	Create the mask image.
private float[][][]	createTensorWeights()	Creates the weighted data for the tensor calculation from the diffusion weighted images.
void	deleteImages()
void	disposeLocal()
ModelImage	getDTI()	Return the DTI Image.
ModelImage	getDWI()
private float[]	readDicomWeight(int iSlice, int iWeight)	Get the slice data for the image with the given slice and weight.
private float	readFloat(byte[] abData, int iIndex)	Translates the byte[] into float values at the given indes iIndex.
private float[]	readFloatWeight(int iSlice, int iWeight)	Get the slice data for the image with the given slice and weight.
private int	readInteger(byte[] abData, int iIndex)	Translates the byte[] into integer values at the given indes iIndex.
private float[]	readIntegerWeight(int iSlice, int iWeight)	Get the slice data for the image with the given slice and weight.
private float[]	readSliceWeight(int iSlice, int iWeight)	Get the slice data for the image with the given slice and weight.
void	runAlgorithm()	Calculate the DTI image.
float[]	solve(Jama.Matrix y, Jama.Matrix m)

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

actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, finalize, 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

m_kMaskImage

private ModelImage m_kMaskImage

Mask Image for masking brain regions during tensor calculation:

m_kDWIImage

private ModelImage m_kDWIImage

DWI Image 4D series of weighted diffusion images

m_kB0Image

private ModelImage m_kB0Image

B0 weighted image:

m_kB0Frame

private ViewJFrameImage m_kB0Frame

ViewJFrameImage for displaying the B0 weighted image:

m_bDisplayB0

private boolean m_bDisplayB0

Whether to just display the B0 weighted image and return, or to do a full calculation:

m_iSlices

private final int m_iSlices

Number of slices in the input images:

m_iDimX

private final int m_iDimX

X Dimension of the input images:

m_iDimY

private final int m_iDimY

Y Dimension of the input images:

m_iBOrig

private final int m_iBOrig

Number of different entries in the BMatrix:

m_iWeights

private final int m_iWeights

Number of images in the weighted series:

m_fMeanNoise

private float m_fMeanNoise

The mean noise value:

m_kBMatrix

private WildMagic.LibFoundation.Mathematics.GMatrixd m_kBMatrix

General matrix storing BMatrix values.

m_aakDWIList

private String[][] m_aakDWIList

List of file names for the Diffusion Weighted Images, from the .path file.

m_aiMatrixEntries

private int[] m_aiMatrixEntries

keeps track of unique entries in the BMatrix

m_kRawImageFormat

private String m_kRawImageFormat

Format of the raw data: (float, int, dicom, etc.)

m_kDTI

private ModelImage m_kDTI

Output DTI Image:

m_bUseDTIParameters

private boolean m_bUseDTIParameters

When true, use the ModelImage DTI parameters.

alg

private AlgorithmBrainSurfaceExtractor alg

handle to BSE Algorithm *

m_3dbufferMap_float

private final HashMap<String,float[]> m_3dbufferMap_float

m_4dbufferMap_float

private final HashMap<String,float[]> m_4dbufferMap_float

m_3dbufferMap_int

private final HashMap<String,int[]> m_3dbufferMap_int

m_4dbufferMap_int

private final HashMap<String,int[]> m_4dbufferMap_int

Constructor Details

AlgorithmDWI2DTI

public AlgorithmDWI2DTI(ModelImage kMaskImage,
 boolean bDisplayB0,
 int iSlices,
 int iDimX,
 int iDimY,
 int iBOrig,
 int iWeights,
 float fMeanNoise,
 String[][] aakDWIList,
 int[] aiMatrixEntries,
 WildMagic.LibFoundation.Mathematics.GMatrixd kBMatrix,
 String kRawFormat)

Create a new AlgorithmDWI2DTI

Parameters:

kMaskImage - mask image masking non-brain regions, if null it is calculated.

bDisplayB0 - when true open and display the B0 weighted image and return.

iSlices - number of slices in the raw data.

iDimX - x-dimensions of the raw data.

iDimY - y-dimensions of the raw data.

iBOrig - number of different entries in the BMatrix.

iWeights - number of weighted series.

fMeanNoise - mean noise value.

aakDWIList - list of file names in the weighted series.

kBMatrix - BMatrix values.

kRawFormat - format string for the raw data.

repidx -

AlgorithmDWI2DTI

public AlgorithmDWI2DTI(ModelImage kDWIImage,
 ModelImage maskImage)

Method Details

algorithmPerformed

public void algorithmPerformed(AlgorithmBase algorithm)

Description copied from interface: AlgorithmInterface

Called after an algorithm this listener is registered to exits (maybe successfully, maybe not). If the algorithm is run in a separate thread, this call will be made within that thread. If not, this call will be made from that same, shared thread.

Specified by:

algorithmPerformed in interface AlgorithmInterface

Parameters:

algorithm - the algorithm which has just completed

calculateDTI

public void calculateDTI(int start,
 int end,
 float[] dtiData,
 float[][][] weightData,
 Jama.Matrix B,
 Jama.Matrix H)

calculateDTIVoxel

public void calculateDTIVoxel(float[] dtiData,
 float[][] dwiData,
 float[][][] weightData,
 int x,
 int y,
 int z,
 Jama.Matrix B)

calculateDTIVoxel2

public void calculateDTIVoxel2(float[] dtiData,
 float[][] dwiData,
 float[][][] weightData,
 int x,
 int y,
 int z,
 Jama.Matrix H,
 int volumeSize)

calculateMatrix

public Jama.Matrix calculateMatrix(Jama.Matrix m)

createDWIImage

public float[] createDWIImage()

Second step in processing the diffusion weighted images. This function is called once the brain extractor is complete. The brain image is transformed into a mask image, which is passed to this function. The mask image limits where the tensor calculations are performed. The tensor is calculated, then the eigen vectors and functional anisotropy images. The DialogDTIColorDisplay is then launched.

Parameters:

kMaskImage - mask image representing the brain.

deleteImages

public void deleteImages()

disposeLocal

public void disposeLocal()

getDTI

public ModelImage getDTI()

Return the DTI Image.

Returns:

the DTI Image.

getDWI

public ModelImage getDWI()

runAlgorithm

public void runAlgorithm()

Calculate the DTI image. If the mask image is null, calculate the mask image first.

Specified by:

runAlgorithm in class AlgorithmBase

solve

public float[] solve(Jama.Matrix y,
 Jama.Matrix m)

createDWI

private void createDWI()

createMaskImage

private void createMaskImage()

Create the mask image. Create an image with the B0 weighted data, if one has not already been created. Next use the JDialogBrainSurfaceExtractor to extract only the brain regions.

createTensorWeights

private float[][][] createTensorWeights()

Creates the weighted data for the tensor calculation from the diffusion weighted images.

Returns:

float[][][] containing the weights used in the tensor calculation.

readDicomWeight

private float[] readDicomWeight(int iSlice,
 int iWeight)

Get the slice data for the image with the given slice and weight.

Parameters:

iSlice - slice to read.

iWeight - weight to read.

Returns:

float[] containing the data.

readFloat

private float readFloat(byte[] abData,
 int iIndex)

Translates the byte[] into float values at the given indes iIndex.

Parameters:

abData - byte[] containing float values.

iIndex - index into the array to get the float from.

Returns:

float value representing 4 bytes starting at abData[iIndex*4].

readFloatWeight

private float[] readFloatWeight(int iSlice,
 int iWeight)

Get the slice data for the image with the given slice and weight. For 3d and 4d non-multifile images, the whole buffer is read in and stored...then slice data is extracted from that buffer

Parameters:

iSlice - slice to read.

iWeight - weight to read.

Returns:

float[] containing the data.

readInteger

private int readInteger(byte[] abData,
 int iIndex)

Translates the byte[] into integer values at the given indes iIndex.

Parameters:

abData - byte[] containing integer values.

iIndex - index into the array to get the float from.

Returns:

integer value representing 4 bytes starting at abData[iIndex*4].

readIntegerWeight

private float[] readIntegerWeight(int iSlice,
 int iWeight)

Get the slice data for the image with the given slice and weight. For 3d and 4d non-multifile images, the whole buffer is read in and stored...then slice data is extracted from that buffer

Parameters:

iSlice - slice to read.

iWeight - weight to read.

Returns:

float[] containing the data.

readSliceWeight

private float[] readSliceWeight(int iSlice,
 int iWeight)

Get the slice data for the image with the given slice and weight.

Parameters:

iSlice - slice to read.

iWeight - weight to read.

Returns:

float[] containing the data.