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Add weights to Patlak linear regression #924

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Add weights to Patlak linear regression #924

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063bd26
Add weights to Patlak linear regression
AnderBiguri Sep 8, 2021
9f0ad01
Change docs for apply_patlak_to_images
AnderBiguri Sep 21, 2021
005a702
improvements on PatlakPlot documentation
KrisThielemans Sep 22, 2021
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1 change: 1 addition & 0 deletions src/include/stir/modelling/PatlakPlot.h
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Original file line number Diff line number Diff line change
Expand Up @@ -139,6 +139,7 @@ class PatlakPlot : public RegisteredParsingObject<PatlakPlot, KineticModel>
float _time_shift; //!< Shifts the time to fit the timing of Plasma Data with the Projection Data.
bool _in_correct_scale; //!< Switch to scale or not the model_matrix to the correct scale, according to the appropriate scale factor.
bool _in_total_cnt; //!< Switch to choose the values of the model to be in total counts or in mean counts.
bool _assume_poisson_distribution; //!< Assume that image is Poisson distributed, and weight linear regression accordingly [1/(counts/int{Cp(t)}^2)]
std::string _blood_data_filename; //!< Name of file in which the input function is stored
PlasmaData _plasma_frame_data; //!< Stores the plasma data into frames for brain studies
std::string _time_frame_definition_filename; //!< name of file to get frame definitions
Expand Down
16 changes: 15 additions & 1 deletion src/modelling_buildblock/PatlakPlot.cxx
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Expand Up @@ -34,6 +34,7 @@ set_defaults()
this->_time_shift=0.;
this->_in_correct_scale=false;
this->_in_total_cnt=false;
this->_assume_poisson_distribution=false;
}

const char * const
Expand Down Expand Up @@ -191,7 +192,7 @@ PatlakPlot::apply_linear_regression(ParametricVoxelsOnCartesianGrid & par_image,
frame_num<=num_frames ; ++frame_num )
{
patlak_x[frame_num-1]=patlak_model_array[1][frame_num]/patlak_model_array[2][frame_num];
weights[frame_num-1]=1;
weights[frame_num-1]=1; // if (_assume_poisson_distribution) handled later in the main loop.
}
{ // Do linear_regression for each voxel // for k j i
float slope=0.F;
Expand Down Expand Up @@ -219,7 +220,19 @@ PatlakPlot::apply_linear_regression(ParametricVoxelsOnCartesianGrid & par_image,
// (remember, these are integrals over the time frame, not single values at discrete t)
for ( frame_num = starting_frame;
frame_num<=num_frames ; ++frame_num )
{
patlak_y[frame_num-1]=dyn_image[frame_num][k][j][i]/patlak_model_array[2][frame_num];
if(this->_assume_poisson_distribution)
{
weights[frame_num-1]=dyn_image[frame_num][k][j][i]/(patlak_model_array[2][frame_num]*patlak_model_array[2][frame_num]);
// if is zero, leave as is, zero weight?
if(weights[frame_num-1]){
weights[frame_num-1]=1/weights[frame_num-1];
}else{
weights[frame_num-1]=0.00001;
}
}
}
// Apply the regression to this pixel
linear_regression(y_intersection, slope,
chi_square,
Expand Down Expand Up @@ -335,6 +348,7 @@ initialise_keymap()
this->parser.add_key("Time Shift", &this->_time_shift);
this->parser.add_key("In total counts", &this->_in_total_cnt);
this->parser.add_key("In correct scale", &this->_in_correct_scale);
this->parser.add_key("Poisson distributed images", &this->_assume_poisson_distribution);
this->parser.add_key("Time Frame Definition Filename", &this->_time_frame_definition_filename);
this->parser.add_stop_key("end Patlak Plot Parameters");
}
Expand Down