// computes the weighted fiducial registration error
double ComputeWeightedFRE ( vtkPoints* X,
vtkPoints* Y,
const Matrix3x3List &CovarianceMatricesMoving,
const Matrix3x3List &CovarianceMatricesFixed,
double FRENormalizationFactor,
Matrix3x3List& WeightMatrices,
const Matrix3x3& rotation,
const itk::Vector<double,3>& translation
)
{
double FRE = 0;
//compute weighting matrices
calculateWeightMatrices( CovarianceMatricesMoving,
CovarianceMatricesFixed,
WeightMatrices,
rotation );
#pragma omp parallel for reduction(+:FRE)
for (unsigned int i = 0; i < WeightMatrices.size(); ++i)
{
//convert to itk data types (nessecary since itk 4 migration)
itk::Vector<double,3> converted_MovingPoint;
double point[3];
X->GetPoint(i,point);
converted_MovingPoint[0] = point[0];
converted_MovingPoint[1] = point[1];
converted_MovingPoint[2] = point[2];
// transform point
itk::Vector<double,3> p = rotation * converted_MovingPoint + translation;
Y->GetPoint(i,point);
p[0] -= point[0];
p[1] -= point[1];
p[2] -= point[2];
//do calculation
const itk::Vector<double,3> D = WeightMatrices.at(i) * p;
FRE += (D[0] * D[0] + D[1] * D[1] + D[2] * D[2]);
}
FRE /= WeightMatrices.size();
FRE = FRENormalizationFactor * sqrt(FRE);
return FRE;
}
// computes the weightmatrix with 2 covariance matrices
// and a given transformation
void calculateWeightMatrices(const Matrix3x3List &X,
const Matrix3x3List &Y,
Matrix3x3List &result,
const Matrix3x3 &rotation)
{
const vnl_matrix_fixed<double, 3, 3> rotation_T = rotation.GetTranspose();
#pragma omp parallel for
for (int i = 0; i < static_cast<int>(X.size()); ++i)
{
const Matrix3x3 w = rotation * X[i] * rotation_T;
result[i] = mitk::AnisotropicRegistrationCommon::CalculateWeightMatrix(w, Y[i]);
}
}
