Package gov.nih.mipav.view.renderer.WildMagic.DTI_FrameWork

Class EstimateTensorLLMSE

java.lang.Object
gov.nih.mipav.view.renderer.WildMagic.DTI_FrameWork.EstimateTensorLLMSE
public class EstimateTensorLLMSE extends Object

  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    private static boolean
    detailedDebugging
     

  • Constructor Summary

    Constructors
    Constructor
    Description
    EstimateTensorLLMSE()
     

  • Method Summary

    Modifier and Type
    Method
    Description
    static float[][][][]
    estimate(float[][][][] DWdata, double[] bvalues, double[][] grads, byte[][][] mask, boolean usePartialEstimates)
    estimate Use LLMSE to estimate tensors from DW imaging data on a voxel-wise basis.
    static ModelImage
    estimate(ModelImage image, ModelImage maskImage, boolean usePartialEstimates)
    Uses LLMSE to estimate tensors from DW imaging data on a voxel-wise basis.
    static ModelImage
    estimate(ModelImage dwiImage, ModelImage mask, WildMagic.LibFoundation.Mathematics.GMatrixd matrix, boolean usePartialEstimates)
     
    static void
    estimateBallAndStickCamino(float[][][][] DWdata, byte[][][] mask, inverters.BallStickInversion dtiFit, float[][][][] ballDiff, float[][][][] ballFrac, float[][][][] stickVec, float[][][][] exitcode, float[][][][] intensity)
     
    private static void
    estimateCamino(float[][][][] DWdata, byte[][][] mask, int dtiType, imaging.DW_Scheme scheme, inverters.DT_Inversion dtiFit, float[][][][] tensors, float[][][][] exitcode, float[][][][] intensity)
     
    static ModelImage
    estimateCamino(ModelImage image, ModelImage maskImage, int dtiType, boolean bSaveExitCode, boolean bDisplayExitCode, boolean bSaveIntensity, boolean bDisplayIntensity, String kOutpuDir)
    Uses Camino algorithms to estimate tensors from DW imaging data on a voxel-wise basis.
    static void
    estimateCaminoRESTORE(float[][][][] DWdata, byte[][][] mask, float[][][] noiseField, float[][][][] tensors, float[][][][] exitcode, float[][][][] intensity, imaging.DW_Scheme DTIscheme)
     
    static void
    estimateCaminoThreeTensor(float[][][][] DWdata, byte[][][] mask, inverters.ThreeTensorInversion dtiFit, float[][][][] mix1, float[][][][] tensors1, float[][][][] mix2, float[][][][] tensors2, float[][][][] mix3, float[][][][] tensors3, float[][][][] exitcode, float[][][][] intensity)
     
    static void
    estimateCaminoTwoTensor(float[][][][] DWdata, byte[][][] mask, inverters.TwoTensorInversion dtiFit, float[][][][] mix1, float[][][][] tensors1, float[][][][] mix2, float[][][][] tensors2, float[][][][] exitcode, float[][][][] intensity)
     
    private static WildMagic.LibFoundation.Mathematics.GMatrixd
    getMatrix(DTIParameters dtiparams)
     
    static void
    main(String[] args)
     
    private static ModelImage
    makeImage(float[][][][] values, String name)
    Creates and returns a ModelImage with the tensor data.
    private static ModelImage
    makeTensorImage(float[][][][] tensors, float[][][][] exitCode, String name)
    Creates and returns a ModelImage with the tensor data.
    static boolean
    test()
     
    static boolean
    test(int count)
     

    Methods inherited from class java.lang.Object

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

  • Field Details

    • detailedDebugging

      private static boolean detailedDebugging

  • Constructor Details

    • EstimateTensorLLMSE

      public EstimateTensorLLMSE()

  • Method Details

    • estimate

      public static float[][][][] estimate(float[][][][] DWdata, double[] bvalues, double[][] grads, byte[][][] mask, boolean usePartialEstimates)
      estimate Use LLMSE to estimate tensors from DW imaging data on a voxel-wise basis. Inputs: DWdata - 4D matrix indexed by [x][y][z][dw] where x,y,z are spatial location and dw is diffusion sensitization. bvalues - a list [dw] of b-values indicating the diffusion sensitization for each volume in the 4th dimension of the input data >0 for DW=yes (in s/mm2) =0 for reference images invalid input: '<'0 for volumes to ignore grads - a set of unit vectors [dw][3] indicating the diffusion weighting for each of the input volumes. Vectors corresponding to reference or ignored volumes are ignored. mask - a boolean mask [x][y][z] indicating which voxels in the volume show be used for tensor estimation. If mask is null, then all voxels are processed. usePartialEstimates - boolean true - if any DW data are infinity, NaN, negative or zero (i.e., impossible values) then these data points will be ignored and a tensor will be computed with the remaining data (provided that at least 6 valid DW values and a reference value are available) false - any voxels with any missing DW data are ignored. Output: return value - set of tensors [x][y][z][6], where the tensor coefficients are ordered by upper triangular convention, i.e., xx,xy,xz,yy,yz,zz Units are in mm2/s. Notes: Voxels for which no tensors are computer are reported as all NaN. Last updated: 8/13/2008 Bennett Landman.

    • estimate

      public static ModelImage estimate(ModelImage dwiImage, ModelImage mask, WildMagic.LibFoundation.Mathematics.GMatrixd matrix, boolean usePartialEstimates)

    • estimate

      public static ModelImage estimate(ModelImage image, ModelImage maskImage, boolean usePartialEstimates)
      Uses LLMSE to estimate tensors from DW imaging data on a voxel-wise basis.
      Parameters:
      image - input DWI images series 4D
      maskImage - input mask image (or null) 3D
      usePartialEstimates - when true if any DW data are infinity, NaN, negative or zero (i.e., impossible values) then these data points will be ignored and a tensor will be computed with the remaining data (provided that at least 6 valid DW values and a reference value are available). When false - any voxels with any missing DW data are ignored.
      Returns:
      ModelImage with tensor data.

    • estimateBallAndStickCamino

      public static void estimateBallAndStickCamino(float[][][][] DWdata, byte[][][] mask, inverters.BallStickInversion dtiFit, float[][][][] ballDiff, float[][][][] ballFrac, float[][][][] stickVec, float[][][][] exitcode, float[][][][] intensity)

    • estimateCamino

      private static void estimateCamino(float[][][][] DWdata, byte[][][] mask, int dtiType, imaging.DW_Scheme scheme, inverters.DT_Inversion dtiFit, float[][][][] tensors, float[][][][] exitcode, float[][][][] intensity)

    • estimateCamino

      public static ModelImage estimateCamino(ModelImage image, ModelImage maskImage, int dtiType, boolean bSaveExitCode, boolean bDisplayExitCode, boolean bSaveIntensity, boolean bDisplayIntensity, String kOutpuDir)
      Uses Camino algorithms to estimate tensors from DW imaging data on a voxel-wise basis.
      Parameters:
      image - input DWI images series 4D
      maskImage - input mask image (or null) 3D
      dtiType - the type of estimation (Linear, Non-Linear, Restore, Weighted-Linear).

    • estimateCaminoRESTORE

      public static void estimateCaminoRESTORE(float[][][][] DWdata, byte[][][] mask, float[][][] noiseField, float[][][][] tensors, float[][][][] exitcode, float[][][][] intensity, imaging.DW_Scheme DTIscheme)

    • estimateCaminoThreeTensor

      public static void estimateCaminoThreeTensor(float[][][][] DWdata, byte[][][] mask, inverters.ThreeTensorInversion dtiFit, float[][][][] mix1, float[][][][] tensors1, float[][][][] mix2, float[][][][] tensors2, float[][][][] mix3, float[][][][] tensors3, float[][][][] exitcode, float[][][][] intensity)

    • estimateCaminoTwoTensor

      public static void estimateCaminoTwoTensor(float[][][][] DWdata, byte[][][] mask, inverters.TwoTensorInversion dtiFit, float[][][][] mix1, float[][][][] tensors1, float[][][][] mix2, float[][][][] tensors2, float[][][][] exitcode, float[][][][] intensity)

    • main

      public static void main(String[] args)

    • test

      public static boolean test()

    • test

      public static boolean test(int count)

    • makeTensorImage

      private static ModelImage makeTensorImage(float[][][][] tensors, float[][][][] exitCode, String name)
      Creates and returns a ModelImage with the tensor data.
      Parameters:
      tensors - tensor data
      name - name of the ModelImage
      Returns:
      new ModelImage.

    • makeImage

      private static ModelImage makeImage(float[][][][] values, String name)
      Creates and returns a ModelImage with the tensor data.
      Parameters:
      name - name of the ModelImage
      tensors - tensor data
      Returns:
      new ModelImage.

    • getMatrix

      private static WildMagic.LibFoundation.Mathematics.GMatrixd getMatrix(DTIParameters dtiparams)