Sinogram.inl

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/*

Copyright (c) 2016-2023, Dr Franck P. Vidal, Bangor University, All rights reserved.
Copyright (c) 2023-present, Prof Franck P. Vidal (franck.vidal@stfc.ac.uk), 
UK Research and Innovation, All rights reserved.


Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.

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this list of conditions and the following disclaimer in the documentation and/or
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names of its contributors may be used to endorse or promote products derived 
from this software without specific prior written permission.

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*/


//******************************************************************************
//  Define
//******************************************************************************


//******************************************************************************
//  Include
//******************************************************************************
#ifndef __FFT_h
#include "gVirtualXRay/FFT.h"
#endif


//******************************************************************************
//  namespace
//******************************************************************************
namespace gVirtualXRay {


template<typename T> Sinogram<T>::Sinogram():
        Image<T>()
{}


template<typename T> Sinogram<T>::Sinogram(const Image<T> anImage):
        Image<T>(anImage)
{}


template<typename T> Sinogram<T>::Sinogram(unsigned int aWidth,
            unsigned int aHeight,
            unsigned int aNumberOfSlices):
        Image<T>(aWidth, aHeight, aNumberOfSlices)
{}


template<typename T> Image<T> Sinogram<T>::getProjectionSet() const
{
    Image<T> projection_set(this->m_width, this->m_number_of_slices, this->m_height);

#ifdef NDEBUG
#ifdef WIN32
        #pragma omp parallel for
#else
        #pragma omp parallel for collapse(2)
#endif
#endif
    for (int angle_id = 0; angle_id < this->m_height; ++angle_id)
    {
        for (int row_projection_id = 0; row_projection_id < this->m_number_of_slices; ++row_projection_id)
        {
            const T* p_input(this->getRawData() + angle_id * this->m_width + row_projection_id * this->m_width * this->m_height);
            T* p_output(projection_set.getRawData() + angle_id * this->m_width * this->m_number_of_slices + this->m_width * row_projection_id);

            std::copy(p_input, p_input + this->m_width, p_output);
        }
    }
    return (projection_set);
}


//------------------------------------------------------------------------------
template<typename T> Image<T> Sinogram<T>::art(double aFirstAngle,
                                               double anAngleStep,
                                               unsigned int aNumberOfIterations,
                                               const char* aDirectory,
                                               void (*aCallback)(const Image<T>*, const Image<T>*, const Image<T>*)) const
//------------------------------------------------------------------------------
{
    unsigned int image_width(2 * floor (this->m_width / (2.0 * std::sqrt(2.0))));

    // Start with a homogenous image
    Image<T> new_estimated_image(image_width, image_width, this->m_number_of_slices, this->getSum() / (image_width * image_width));
    Image<T> old_estimated_image(image_width, image_width, this->m_number_of_slices, this->getSum() / (image_width * image_width));

    Image<T> error_back_projection;
    
    double old_ncc(0.0);

    unsigned int iteration(1);
    bool stop(false);
    while (!stop)
    {
        old_estimated_image = new_estimated_image;
    
        // Process every angle
        double angle(aFirstAngle);
        for (unsigned int angle_id(0); angle_id < this->m_height; ++angle_id, angle += anAngleStep)
        {
            // Compute the projections
            Image<T> estimated_projection(new_estimated_image.radonTransform(angle, 0.0, angle).setCanvasSize(this->m_width, 1, this->m_number_of_slices));
            //double sum_estimated(estimated_projection.getSum());

            // Real image
            Image<T> real_projection(this->getROI(0, angle_id, 0, this->m_width, 1, this->m_number_of_slices));

            // Compute the error
            Sinogram<T> error_in_projections = (real_projection - estimated_projection);
        
            // Correct for errors
            error_back_projection = error_in_projections.simpleBackProjection(angle, angle);
        
            new_estimated_image += error_back_projection.setCanvasSize(image_width, image_width, this->m_number_of_slices);

            T* p_temp(new_estimated_image.getRawData());
            for (unsigned int i(0); i < new_estimated_image.getWidth() * new_estimated_image.getHeight() * new_estimated_image.getDepth(); ++i, ++p_temp)
            {
                *p_temp = std::max(0.0f, *p_temp);
            }

            if (aDirectory)
            {
                std::stringstream filename;
                filename << aDirectory << "/iteration_" << iteration << "_" << angle_id << ".mha";
                (new_estimated_image.setCanvasSize(image_width, image_width, this->m_number_of_slices).normalised() * 255).savePGM(filename.str());
            }
            
            if (aCallback)
            {
                (*aCallback)(&new_estimated_image, &estimated_projection, &error_back_projection);
            }
        }

        // Compute the projection
        Image<T> estimated_projections(new_estimated_image.radonTransform(aFirstAngle, anAngleStep, this->m_height).setCanvasSize(this->m_width, this->m_height, this->m_number_of_slices));

        // Stopping criteria
        double ncc_projections(100.0 * this->computeNCC(estimated_projections));
        double ncc_reconstructions(100.0 * new_estimated_image.computeNCC(old_estimated_image));

        if ((ncc_projections  > 99.50 || ncc_reconstructions > 99.50) /*&& std::abs(old_ncc - ncc_reconstructions) < EPSILON*/)
        {
            stop = true;
        }
        else if (aNumberOfIterations == iteration)
        {
            stop = true;
        }

        old_ncc = ncc_reconstructions;

        iteration++;

        
        if (aCallback)
        {
            (*aCallback)(&new_estimated_image, &estimated_projections, &error_back_projection);
        }
    }
    
    return (new_estimated_image.setCanvasSize(image_width, image_width, this->m_number_of_slices));
}


//-------------------------------------------------------------------------------
template<typename T> Image<T> Sinogram<T>::mart(double aFirstAngle,
                                                double anAngleStep,
                                                unsigned int aNumberOfIterations,
                                                const char* aDirectory,
                                                void (*aCallback)(const Image<T>*, const Image<T>*, const Image<T>*)) const
//-------------------------------------------------------------------------------
{
    unsigned int image_width(2 * floor (this->m_width / (2.0 * std::sqrt(2.0))));

    // Start with a homogenous image
    Image<T> new_estimated_image(image_width, image_width, this->m_number_of_slices, this->getSum() / (image_width * image_width));
    Image<T> old_estimated_image(image_width, image_width, this->m_number_of_slices, this->getSum() / (image_width * image_width));

    Image<T> error_back_projection;
    
    double old_ncc(0.0);

    unsigned int iteration(1);
    bool stop(false);
    while (!stop)
    {
        old_estimated_image = new_estimated_image;
    
        // Process every angle
        double angle(aFirstAngle);
        for (unsigned int angle_id(0); angle_id < this->m_height; ++angle_id, angle += anAngleStep)
        {
            // Compute the projections
            Image<T> estimated_projection(new_estimated_image.radonTransform(angle, 0.0, angle).setCanvasSize(this->m_width, 1, this->m_number_of_slices));
            //double sum_estimated(estimated_projection.getSum());

            // Real image
            Image<T> real_projection(this->getROI(0, angle_id, 0, this->m_width, 1, this->m_number_of_slices));

            // Compute the error
            Sinogram<T> error_in_projections(real_projection - estimated_projection);
        
            // Correct for errors
            error_back_projection = Image<T>(error_in_projections.simpleBackProjection(angle, angle));
        
            new_estimated_image *= error_back_projection.setCanvasSize(image_width, image_width, this->m_number_of_slices);

            T* p_temp(new_estimated_image.getRawData());
            for (unsigned int i(0); i < new_estimated_image.getWidth() * new_estimated_image.getHeight() * new_estimated_image.getDepth(); ++i, ++p_temp)
            {
                *p_temp = std::max(0.0f, *p_temp);
            }

            if (aDirectory)
            {
                std::stringstream filename;
                filename << aDirectory << "/iteration_" << iteration << "_" << angle_id << ".mha";
                (new_estimated_image.setCanvasSize(image_width, image_width, this->m_number_of_slices).normalised() * 255).savePGM(filename.str());
            }
            
            if (aCallback)
            {
                (*aCallback)(&new_estimated_image, &estimated_projection, &error_back_projection);
            }
        }

        // Compute the projection
        Image<T> estimated_projections(new_estimated_image.radonTransform(aFirstAngle, anAngleStep, this->m_height).setCanvasSize(this->m_width, this->m_height, this->m_number_of_slices));

        // Stopping criteria
        double ncc_projections(100.0 * this->computeNCC(estimated_projections));
        double ncc_reconstructions(100.0 * new_estimated_image.computeNCC(old_estimated_image));

        if ((ncc_projections  > 99.50 || ncc_reconstructions > 99.50) /*&& std::abs(old_ncc - ncc_reconstructions) < EPSILON*/)
        {
            stop = true;
        }
        else if (aNumberOfIterations == iteration)
        {
            stop = true;
        }

        old_ncc = ncc_reconstructions;

        iteration++;

        
        if (aCallback)
        {
            (*aCallback)(&new_estimated_image, &estimated_projections, &error_back_projection);
        }
    }
    
    return (new_estimated_image.setCanvasSize(image_width, image_width, this->m_number_of_slices));
}


//-------------------------------------------------------------------------------
template<typename T> Image<T> Sinogram<T>::sirt(double aFirstAngle,
                                                double anAngleStep,
                                                unsigned int aNumberOfIterations,
                                                const char* aDirectory,
                                                void (*aCallback)(const Image<T>*, const Image<T>*, const Image<T>*)) const
//-------------------------------------------------------------------------------
{
    unsigned int image_width(2 * floor (this->m_width / (2.0 * std::sqrt(2.0))));

    // Start with a homogenous image
    Image<T> new_estimated_image(image_width, image_width, this->m_number_of_slices, this->getSum() / (image_width * image_width));
    Image<T> old_estimated_image(image_width, image_width, this->m_number_of_slices, this->getSum() / (image_width * image_width));

    //std::cout << this->getSum() << "\t" << new_estimated_image.getSum() << std::endl;
    double old_ncc(0.0);

    unsigned int iteration(1);
    bool stop(false);
    while (!stop)
    {
        old_estimated_image = new_estimated_image;

        Image<T> estimated_projection(new_estimated_image.radonTransform(aFirstAngle, anAngleStep, this->m_height));

        // Compute the error
        Sinogram<T> error_in_projections(*this - estimated_projection);

        this->saveASCII("real_projection.mat");
        estimated_projection.saveASCII("estimated_projection.mat");
        error_in_projections.saveASCII("error_in_projections.mat");

        Image<T> error_back_projection(error_in_projections.simpleBackProjection(aFirstAngle, anAngleStep));
        error_back_projection.saveASCII("error_back_projection.mat");

        // Correct for errors
        new_estimated_image += error_back_projection.setCanvasSize(image_width, image_width, this->m_number_of_slices);
        new_estimated_image.saveASCII("new_estimated_image.mat");
        old_estimated_image.saveASCII("old_estimated_image.mat");

        T* p_temp(new_estimated_image.getRawData());
        for (unsigned int i(0); i < new_estimated_image.getWidth() * new_estimated_image.getHeight() * new_estimated_image.getDepth(); ++i, ++p_temp)
        {
            *p_temp = std::max(0.0f, *p_temp);
        }

        if (aDirectory)
        {
            std::stringstream filename;
            filename << aDirectory << "/iteration_" << iteration << ".mha";
            (new_estimated_image.setCanvasSize(image_width, image_width, this->m_number_of_slices).normalised() * 255).savePGM(filename.str());
        }

        
        if (aCallback)
        {
            (*aCallback)(&new_estimated_image, &estimated_projection, &error_back_projection);
        }

        // Compute the projection
        Image<T> estimated_projections(new_estimated_image.radonTransform(aFirstAngle, anAngleStep, this->m_height).setCanvasSize(this->m_width, this->m_height, this->m_number_of_slices));
        estimated_projections.saveASCII("simulated_projection.mat");

        // Stopping criteria
        double ncc_projections(100.0 * this->computeNCC(estimated_projections));
        double ncc_reconstructions(100.0 * new_estimated_image.computeNCC(old_estimated_image));

        if ((ncc_projections  > 99.50 || ncc_reconstructions > 99.50) /*&& std::abs(old_ncc - ncc_reconstructions) < EPSILON*/)
        {
            stop = true;
        }
        else if (aNumberOfIterations == iteration)
        {
            stop = true;
        }

        old_ncc = ncc_reconstructions;

        iteration++;

    }

    return (new_estimated_image.setCanvasSize(image_width, image_width, this->m_number_of_slices));
}


//-------------------------------------------------------------------------------------------
template<typename T> Image<T> Sinogram<T>::simpleBackProjection(double aFirstAngle,
                                                                double anAngleStep,
                                                                const char* aDirectory,
                                                                void (*aCallback)(const Image<T>*, const Image<T>*, const Image<T>*)) const
//-------------------------------------------------------------------------------------------
{
    Image<T> sinogram(this->resize(this->m_width * 2, this->m_height, this->m_number_of_slices));
    sinogram.saveASCII("resized.mat");
    unsigned int image_width(2 * floor (sinogram.getWidth() / (2.0 * std::sqrt(2.0))));

    Image<T> reconstruction(sinogram.getWidth(), sinogram.getWidth(), sinogram.getDepth());

    double angle(aFirstAngle);
    for (unsigned int angle_id(0);
            angle_id < this->m_height;
            ++angle_id, angle += anAngleStep)
    {
        Image<T> back_projection(sinogram.getWidth(), sinogram.getWidth(), sinogram.getDepth());

#ifdef NDEBUG
#ifdef WIN32
        #pragma omp parallel for
#else
        #pragma omp parallel for collapse(3)
#endif
#endif
        for (int k = 0; k < reconstruction.getDepth(); ++k)
        {
            for (int j = 0; j < reconstruction.getHeight(); ++j)
            {
                for (int i = 0; i < reconstruction.getWidth(); ++i)
                {
                    back_projection(i, j, k) += sinogram.getPixel(i, angle_id, k);
                }
            }
        }

        reconstruction += back_projection.rotate(-angle) / reconstruction.getHeight();

        if (aDirectory)
        {
            std::stringstream filename;
            filename << aDirectory << "/angle_" << angle_id << ".mha";
            (reconstruction.setCanvasSize(image_width, image_width, reconstruction.getDepth()).resize(image_width / 2, image_width / 2, reconstruction.getDepth()).normalised() * 255).savePGM(filename.str());
        }

        
        if (aCallback)
        {
            (*aCallback)(&reconstruction, &back_projection, this);
        }
    }

    //reconstruction = reconstruction.rotate(-angle);

    reconstruction = reconstruction.setCanvasSize(image_width, image_width, this->m_number_of_slices);
    reconstruction *= Pi / (/*2.0 * */ this->getHeight());

    return (reconstruction.resize(image_width / 2, image_width / 2, this->getDepth()));
}


//---------------------------------------------------------------------------------------------
template<typename T> Image<T> Sinogram<T>::filteredBackProjection(double aFirstAngle,
                                                                  double anAngleStep,
                                                                  const char* aFilterType,
                                                                  float aScalingFactor,
                                                                  const char* aDirectory,
                                                                  void (*aCallback)(const Image<T>*, const Image<T>*, const Image<T>*)) const
//---------------------------------------------------------------------------------------------
{
    typedef  FFT<T>   FAST_FOURIER_TRANSFORM;

    // Compute the FFTs
    std::vector<FAST_FOURIER_TRANSFORM> p_fft_set;
    for (unsigned int j(0); j < this->m_height; ++j)
    {
        p_fft_set.push_back(this->getROI(0, j, 0, this->m_width, 1, this->m_number_of_slices).getFFT());
    }

    // Compute the rho filter
    for (typename std::vector<FAST_FOURIER_TRANSFORM>::iterator ite(p_fft_set.begin());
            ite != p_fft_set.end();
            ++ite)
    {
        *ite = ite->rhoFilter(aFilterType, aScalingFactor);
    }

    // Compute the iFFTs
    std::vector<Image<T> > p_ifft_set(this->m_height);
    for (unsigned int j(0); j < this->m_height; ++j)
    {
        p_ifft_set[j] = p_fft_set[j].getInverseFFT();
    }

    // Store the results
    Sinogram<T> filtered_sinogram(this->m_width, this->m_height, this->m_number_of_slices);

    for (unsigned int k(0); k < this->m_number_of_slices; ++k)
    {
        for (unsigned int j(0); j < this->m_height; ++j)
        {
            for (unsigned int i(0); i < this->m_width; ++i)
            {
                filtered_sinogram(i, j, k) = p_ifft_set[j](i, 0, k);
            }
        }
    }

    //std::cout << getAverage() << "  " << filtered_sinogram.getAverage() << std::endl;
    //filtered_sinogram *= filtered_sinogram.getAverage() / getAverage();
    //filtered_sinogram.saveASCII("filtered_sinogram.mat");
    return (filtered_sinogram.simpleBackProjection(aFirstAngle,
                                                   anAngleStep,
                                                   aDirectory,
                                                   aCallback));
}


//---------------------------------------------------------------------------------
template<typename T> Image<T> Sinogram<T>::art(double aFirstAngle,
                                               double anAngleStep, 
                                               unsigned int aNumberOfIterations, 
                                               const std::string& aDirectory,
                                               void (*aCallback)(const Image<T>*, const Image<T>*, const Image<T>*)) const
//---------------------------------------------------------------------------------
{
    return (art(aFirstAngle,
                anAngleStep,
                aNumberOfIterations,
                aDirectory.data(),
                aCallback));
}


//----------------------------------------------------------------------------------
template<typename T> Image<T> Sinogram<T>::mart(double aFirstAngle,
                                                double anAngleStep,
                                                unsigned int aNumberOfIterations,
                                                const std::string& aDirectory,
                                                void (*aCallback)(const Image<T>*, const Image<T>*, const Image<T>*)) const
//----------------------------------------------------------------------------------
{
    return (mart(aFirstAngle,
                 anAngleStep,
                 aNumberOfIterations,
                 aDirectory.data(),
                 aCallback));
}


//----------------------------------------------------------------------------------
template<typename T> Image<T> Sinogram<T>::sirt(double aFirstAngle,
                                                double anAngleStep,
                                                unsigned int aNumberOfIterations,
                                                const std::string& aDirectory,
                                                void (*aCallback)(const Image<T>*, const Image<T>*, const Image<T>*)) const
//----------------------------------------------------------------------------------
{
    return (sirt(aFirstAngle,
                 anAngleStep,
                 aNumberOfIterations,
                 aDirectory.data(),
                 aCallback));
}


//--------------------------------------------------------------------------------------------------
template<typename T> Image<T> Sinogram<T>::simpleBackProjection(double aFirstAngle,
                                                                double anAngleStep,
                                                                const std::string& aDirectory,
                                                                void (*aCallback)(const Image<T>*, const Image<T>*, const Image<T>*)) const
//--------------------------------------------------------------------------------------------------
{
    return (simpleBackProjection(aFirstAngle,
                                 anAngleStep,
                                 aDirectory.data(),
                                 aCallback));
}


//----------------------------------------------------------------------------------------------------
template<typename T> Image<T> Sinogram<T>::filteredBackProjection(double aFirstAngle,
                                                                  double anAngleStep,
                                                                  const std::string& aFilterType,
                                                                  float aScalingFactor,
                                                                  const std::string& aDirectory,
                                                                  void (*aCallback)(const Image<T>*, const Image<T>*, const Image<T>*)) const
//----------------------------------------------------------------------------------------------------
{
    return (filteredBackProjection(aFirstAngle,
                                   anAngleStep,
                                   aFilterType.data(),
                                   aScalingFactor,
                                   aDirectory.data(),
                                   aCallback));
}


} // namespace gVirtualXRay