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

Class CAAMLinearReg

  • public class CAAMLinearReg
extends CAAMObject
    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 $ Performs multi-variate linear regression on a set of experiments.
    Author:
    Ruida Cheng

    • Field Detail

      • m_nExperiments

        private int m_nExperiments
        number of experiments.

      • m_nPixelsDiffs

        private int m_nPixelsDiffs
        number of pixel difference.

      • m_nParams

        private int m_nParams
        number of parameters.

      • m_vEigenVal

        private CDVector m_vEigenVal
        eigen value vector.

      • m_mEigenVec

        private CDMatrix m_mEigenVec
        eigen value matrix.

    • Constructor Detail

      • CAAMLinearReg

        public CAAMLinearReg()
        constructor

    • Method Detail

      • dispose

        public void dispose()
        dispose memory

      • EstimateK

        private int EstimateK​(CDMatrix C,
                      CDMatrix EigenVec_k,
                      CDMatrix EigenVal_k)
        Performs k-estimation.
        Parameters:
        C - The parameter matrix.
        EigenVec_k - Output k eigenvectors.
        EigenVal_k - Output k eigenvalues.
        Returns:
        k

      • DoRegression

        public int DoRegression​(CDMatrix C,
                        CDMatrix X,
                        CDMatrix R)
        Calculates the regression matrix, R from the set of experiments in C and X, obtaining the relationship: C = RX.
        Parameters:
        C - In the AAM case: the input parameters displacements.
        X - In the AAM case: the input normalized pixel differences.
        R - The output regression matrix.
        Returns:
        k

      • VisDMatrixSymmetricEigen

        public boolean VisDMatrixSymmetricEigen​(CVisDMatrix A,
                                        CVisDVector vals,
                                        CVisDMatrix vects)
        Symmetric eigen analysis
        Parameters:
        A -
        vals -
        vects -
        Returns:

      • Dsyev

        public int Dsyev​(int m,
                 double[][] a,
                 double[] vals,
                 double[][] vects)
        Call lapack routine
        Parameters:
        m -
        a -
        vals -
        vects -
        Returns: