java.lang.Object
- gov.nih.mipav.view.renderer.WildMagic.AAM.CAAMMathUtil

```
public class CAAMMathUtil
extends java.lang.Object
```
This is the Java modified version of C++ active appearance model API (AAM_API). It is modified with a subset of required functions for automatic MRI prostate segmentation. AAM-API LICENSE - file: license.txt This software is freely available for non-commercial use such as research and education. Please see the full disclaimer below. All publications describing work using this software should cite the reference given below. Copyright (c) 2000-2003 Mikkel B. Stegmann, mbs@imm.dtu.dk IMM, Informatics & Mathematical Modelling DTU, Technical University of Denmark Richard Petersens Plads, Building 321 DK-2800 Lyngby, Denmark http://www.imm.dtu.dk/~aam/ REFERENCES Please use the reference below, when writing articles, reports etc. where the AAM-API has been used. A draft version the article is available from the homepage. I will be happy to receive pre- or reprints of such articles. /Mikkel ------------- M. B. Stegmann, B. K. Ersboll, R. Larsen, "FAME -- A Flexible Appearance Modelling Environment", IEEE Transactions on Medical Imaging, IEEE, 2003 (to appear) ------------- 3RD PART SOFTWARE The software is partly based on the following libraries: - The Microsoft(tm) Vision Software Developers Kit, VisSDK - LAPACK DISCLAIMER This software is provided 'as-is', without any express or implied warranty. In no event will the author be held liable for any damages arising from the use of this software. Permission is granted to anyone to use this software for any non-commercial purpose, and to alter it, subject to the following restrictions: 1. The origin of this software must not be misrepresented; you must not claim that you wrote the original software. 2. Altered source versions must be plainly marked as such, and must not be misrepresented as being the original software. 3. This notice may not be removed or altered from any source distribution. -- No guarantees of performance accompany this software, nor is any responsibility assumed on the part of the author or IMM. This software is provided by Mikkel B. Stegmann and IMM ``as is'' and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. In no event shall IMM or Mikkel B. Stegmann be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage. $Revision: 1.4 $ $Date: 2003/04/23 14:49:15 $ Utility math/statistical methods for the AAM project. This is the mathematical / statistical garbage bin. It consists of methods that for some reason haven't found its way into other (and more meaningful) classes. methods are static, so there is never need for an instantiation of this class.

Author:

Ruida Cheng

Constructor Summary

Constructors
Constructor Description

CAAMMathUtil()

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`static void`	`CalcElementVar(java.util.Vector<CDVector> vVectors, CDVector varVec)`	Wrapper to calculate element variables.
`static void`	`CalcElementVar(java.util.Vector<CDVector> vVectors, CDVector varVec, CDVector vpMean)`	Calculates the variance of each component in a set of vectors.
`void`	`CumSum(CDVector v, CDVector cumsum, boolean normalize)`	Cumulative sum of elements.
`void`	`ExpandMatrix2DyadicSize(CDMatrix m, CDMatrix dyad)`	This method expands a matrix to have dynamic size, i.e. nrows and ncols that are powers of two.
`void`	`GaussianHistogramMatching(CDVector v, CDVector out, int nbins, CDVector gaussLUT)`	Maps the distibution of v into an approximate Gaussian distribution.
`static void`	`Hist(CDVector v, double min, double max, CDVector hist, int nbins, boolean normalize, boolean transform)`	Calculates the histogram of a vector within [min;max] with optional nomalization.
`void`	`LinearStretchClamp(CDVector v, double x1, double x2, double new_min, double new_max)`	Maps a vector linearly from [x1;x2] to [new_min;new_max].
`static void`	`LinearStretchMinMax(CDVector v, double new_min, double new_max)`	Maps a vector linearly from [min;max] to [new_min;new_max].
`void`	`MeanFilter(CDMatrix in, CDMatrix out)`	Performs a 3x3 mean filtering of a matrix.
`static double`	`MutualInformation(CDVector v1, CDVector v2, int nbins)`	Calulates the Mutual Information (MI) between two vectors.
`void`	`PseudoInv(CDMatrix A, CDMatrix P)`	Calculates the pseudo inverse of a matrix.
`static void`	`ZeroMeanUnitLength(CDVector v)`	Normalises a vector to zero mean and unit length.

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

- Constructor Detail
  - CAAMMathUtil
```
public CAAMMathUtil()
```
- Method Detail
  - Hist
```
public static void Hist(CDVector v,
                        double min,
                        double max,
                        CDVector hist,
                        int nbins,
                        boolean normalize,
                        boolean transform)
```
    Calculates the histogram of a vector within [min;max] with optional nomalization.
    
    Parameters:
    
    v - Input vector.
    
    min - Value for the first bin (values lower are clamped to min).
    
    max - Value for the last bin (values lower are clamped to max).
    
    hist - Output histogram vector.
    
    nbins - The number of bins. Default 256.
    
    normalize - Optional normalization, i.e. make the histogram entries sum to 1. Default true.
    
    transform - Optional transformation of v into 'nbins' integer intervals between [min;max]. Default false.
  - CumSum
```
public void CumSum(CDVector v,
                   CDVector cumsum,
                   boolean normalize)
```
    Cumulative sum of elements.
    
    Parameters:
    
    v - Input vector.
    
    cumsum - Output vector containing the cumulative sum of elements.
    
    normalize - Optional normalization of output, i.e. cumsum[end] = 1.0. Default true.
  - MutualInformation
```
public static double MutualInformation(CDVector v1,
                                       CDVector v2,
                                       int nbins)
```
    Calulates the Mutual Information (MI) between two vectors. See e.g. C. Studholme et al. or Viola et al.
    
    Parameters:
    
    v1 - Signal 1.
    
    v2 - Signal 2.
    
    nbins - The number of bins in the single and joint histograms. Default 256.
    
    Returns:
    
    The Mutual Information (MI).
  - GaussianHistogramMatching
```
public void GaussianHistogramMatching(CDVector v,
                                      CDVector out,
                                      int nbins,
                                      CDVector gaussLUT)
```
    Maps the distibution of v into an approximate Gaussian distribution.
    
    Parameters:
    
    v - Input vector.
    
    out - Output vector.
    
    nbins - Number of bins used to approx the distribution. Default 256.
    
    gaussLUT - If not null, the calulated LUT is returned here.
  - ExpandMatrix2DyadicSize
```
public void ExpandMatrix2DyadicSize(CDMatrix m,
                                    CDMatrix dyad)
```
    This method expands a matrix to have dynamic size, i.e. nrows and ncols that are powers of two. Expansion are done using zero-padding.
    
    Parameters:
    
    m - Input matrix.
    
    dyad - Output dynamic version.
  - CalcElementVar
```
public static void CalcElementVar(java.util.Vector<CDVector> vVectors,
                                  CDVector varVec)
```
    Wrapper to calculate element variables.
    
    Parameters:
    
    vVectors - Input set of vectors.
    
    varVec - A vector containing the variance of each component in cVectors.
  - CalcElementVar
```
public static void CalcElementVar(java.util.Vector<CDVector> vVectors,
                                  CDVector varVec,
                                  CDVector vpMean)
```
    Calculates the variance of each component in a set of vectors.
    
    Parameters:
    
    cVectors - Input set of vectors.
    
    varVec - A vector containing the variance of each component in cVectors.
    
    vpMean - Optional vector pointer to return the mean vector in.
  - LinearStretchMinMax
```
public static void LinearStretchMinMax(CDVector v,
                                       double new_min,
                                       double new_max)
```
    Maps a vector linearly from [min;max] to [new_min;new_max].
    
    Parameters:
    
    v - Input vector.
    
    new_min - Desired minimum.
    
    new_max - Desired maximum.
  - LinearStretchClamp
```
public void LinearStretchClamp(CDVector v,
                               double x1,
                               double x2,
                               double new_min,
                               double new_max)
```
    Maps a vector linearly from [x1;x2] to [new_min;new_max]. Values outside [x1;x2] are clamped to x1, x2 respectively.
    
    Parameters:
    
    v - Input vector.
    
    x1 - Starting point of stretch.
    
    x2 - Ending point of stretch.
    
    new_min - Desired minimum.
    
    new_max - Desired maximum.
  - MeanFilter
```
public void MeanFilter(CDMatrix in,
                       CDMatrix out)
```
    Performs a 3x3 mean filtering of a matrix.
    
    Parameters:
    
    in - Input matrix.
    
    out - Output mean filtered matrix.
  - ZeroMeanUnitLength
```
public static void ZeroMeanUnitLength(CDVector v)
```
    Normalises a vector to zero mean and unit length.
    
    Parameters:
    
    v - Input vector.
  - PseudoInv
```
public void PseudoInv(CDMatrix A,
                      CDMatrix P)
```
    Calculates the pseudo inverse of a matrix.
    
    Parameters:
    
    A - Input matrix.
    
    P - Pseudo inverse of A.

Class CAAMMathUtil

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

CAAMMathUtil

Method Detail

Hist

CumSum

MutualInformation

GaussianHistogramMatching

ExpandMatrix2DyadicSize

CalcElementVar

CalcElementVar

LinearStretchMinMax

LinearStretchClamp

MeanFilter

ZeroMeanUnitLength

PseudoInv