typename AstroStickModel< ScalarType >::PixelType AstroStickModel< ScalarType >::SimulateMeasurement()
{
PixelType signal;
signal.SetSize(this->m_GradientList.size());
double b = -m_BValue*m_Diffusivity;
if (m_RandomizeSticks)
m_NumSticks = 30 + m_RandGen->GetIntegerVariate()%31;
for( unsigned int i=0; i<this->m_GradientList.size(); i++)
{
GradientType g = this->m_GradientList[i];
double bVal = g.GetNorm(); bVal *= bVal;
if (bVal>0.0001)
{
for (int j=0; j<m_NumSticks; j++)
{
double dot = 0;
if(m_RandomizeSticks)
dot = GetRandomDirection()*g;
else
dot = m_Sticks[j]*g;
signal[i] += exp( b*bVal*dot*dot );
}
signal[i] /= m_NumSticks;
}
else
signal[i] = 1;
}
return signal;
}
typename TensorModel< ScalarType >::PixelType TensorModel< ScalarType >::SimulateMeasurement()
{
PixelType signal;
signal.SetSize(this->m_GradientList.size());
signal.Fill(0.0);
ItkTensorType tensor;
tensor.Fill(0.0);
this->m_FiberDirection.Normalize();
vnl_vector_fixed<double, 3> axis = itk::CrossProduct(m_KernelDirection, this->m_FiberDirection).GetVnlVector();
axis.normalize();
vnl_quaternion<double> rotation(axis, acos(m_KernelDirection*this->m_FiberDirection));
rotation.normalize();
vnl_matrix_fixed<double, 3, 3> matrix = rotation.rotation_matrix_transpose();
vnl_matrix_fixed<double, 3, 3> tensorMatrix = matrix.transpose()*m_KernelTensorMatrix*matrix;
tensor[0] = tensorMatrix[0][0];
tensor[1] = tensorMatrix[0][1];
tensor[2] = tensorMatrix[0][2];
tensor[3] = tensorMatrix[1][1];
tensor[4] = tensorMatrix[1][2];
tensor[5] = tensorMatrix[2][2];
for( unsigned int i=0; i<this->m_GradientList.size(); i++)
{
GradientType g = this->m_GradientList[i];
ScalarType bVal = g.GetNorm();
bVal *= bVal;
if (bVal>0.0001)
{
itk::DiffusionTensor3D< ScalarType > S;
S[0] = g[0]*g[0];
S[1] = g[1]*g[0];
S[2] = g[2]*g[0];
S[3] = g[1]*g[1];
S[4] = g[2]*g[1];
S[5] = g[2]*g[2];
ScalarType D = tensor[0]*S[0] + tensor[1]*S[1] + tensor[2]*S[2] +
tensor[1]*S[1] + tensor[3]*S[3] + tensor[4]*S[4] +
tensor[2]*S[2] + tensor[4]*S[4] + tensor[5]*S[5];
// check for corrupted tensor and generate signal
if (D>=0)
signal[i] = exp ( -m_BValue * bVal * D );
}
else
signal[i] = 1;
}
return signal;
}
typename BallModel< ScalarType >::PixelType BallModel< ScalarType >::SimulateMeasurement()
{
PixelType signal;
signal.SetSize(this->m_GradientList.size());
for( unsigned int i=0; i<this->m_GradientList.size(); i++)
{
GradientType g = this->m_GradientList[i];
if (g.GetNorm()>0.0001)
signal[i] = exp( -m_BValue * m_Diffusivity );
else
signal[i] = 1;
}
return signal;
}
typename StickModel< ScalarType >::PixelType StickModel< ScalarType >::SimulateMeasurement(GradientType &fiberDirection)
{
PixelType signal;
signal.SetSize(this->m_GradientList.size());
for( unsigned int i=0; i<this->m_GradientList.size(); i++)
{
GradientType g = this->m_GradientList[i];
if (g.GetNorm()>0.0001)
{
ScalarType dot = fiberDirection*g;
signal[i] = std::exp( -this->m_BValue*m_Diffusivity*dot*dot ); // skip * bVal becaus bVal is already encoded in the dot product (norm of g encodes b-value relative to baseline b-value m_BValue)
}
else
signal[i] = 1;
}
return signal;
}
typename StickModel< ScalarType >::PixelType StickModel< ScalarType >::SimulateMeasurement()
{
PixelType signal;
signal.SetSize(this->m_GradientList.size());
for( unsigned int i=0; i<this->m_GradientList.size(); i++)
{
GradientType g = this->m_GradientList[i];
double bVal = g.GetNorm(); bVal *= bVal;
if (bVal>0.0001)
{
double dot = this->m_FiberDirection*g;
signal[i] = exp( -m_BValue * bVal * m_Diffusivity*dot*dot );
}
else
signal[i] = 1;
}
return signal;
}