stir_x.h

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/*
SyneRBI Synergistic Image Reconstruction Framework (SIRF)
Copyright 2015 - 2021 Rutherford Appleton Laboratory STFC
Copyright 2019 - 2021 University College London
 
This is software developed for the Collaborative Computational
Project in Synergistic Reconstruction for Biomedical Imaging (formerly CCP PETMR)
(http://www.ccpsynerbi.ac.uk/).
 
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
 
*/
 
#ifndef EXTRA_STIR_TYPES
#define EXTRA_STIR_TYPES
 
#define WIN32_LEAN_AND_MEAN
 
#include <cmath>
#include <stdlib.h>
 
#include "sirf/common/iequals.h"
#include "sirf/common/JacobiCG.h"
#include "sirf/STIR/stir_data_containers.h"
#include "stir/recon_buildblock/PoissonLogLikelihoodWithLinearModelForMeanAndProjData.h"
 
#define MIN_BIN_EFFICIENCY 1.0e-20f
//#define MIN_BIN_EFFICIENCY 1.0e-6f
#define SIRF_DYNAMIC_CAST(T, X, Y) T& X = dynamic_cast<T&>(Y)
 
namespace sirf {
 
    class ListmodeToSinograms : public stir::LmToProjData {
    public:
 
        //ListmodeToSinograms(const char* const par) : stir::LmToProjData(par) {}
        ListmodeToSinograms(const char* par) : stir::LmToProjData(par) {}
        ListmodeToSinograms() : stir::LmToProjData()
        {
                        set_defaults();
            fan_size = -1;
            store_prompts = true;
            store_delayeds = false;
            delayed_increment = 0;
            num_iterations = 10;
            display_interval = 1;
            KL_interval = 1;
            save_interval = -1;
            //num_events_to_store = -1;
        }
        void set_input(std::string lm_file)
        {
            input_filename = lm_file;
                        lm_data_ptr = stir::read_from_file<ListModeData>(input_filename);
                        exam_info_sptr_.reset(new ExamInfo(lm_data_ptr->get_exam_info()));
                        proj_data_info_sptr_.reset(lm_data_ptr->get_proj_data_info_sptr()->clone());
        }
 
        void set_output(std::string proj_data_file)
        {
            output_filename_prefix = proj_data_file;
        }
        void set_template(std::string proj_data_file)
        {
                        STIRAcquisitionDataInFile acq_data_template(proj_data_file.c_str());
                        set_template(acq_data_template);
        }
        void set_template(const STIRAcquisitionData& acq_data_template)
        {
                        template_proj_data_info_ptr =
                          acq_data_template.get_proj_data_info_sptr()->create_shared_clone();
        }
        void set_time_interval(double start, double stop)
        {
            std::pair<double, double> interval(start, stop);
            std::vector < std::pair<double, double> > intervals;
            intervals.push_back(interval);
            frame_defs = stir::TimeFrameDefinitions(intervals);
            do_time_frame = true;
        }
        int set_flag(const char* flag, bool value)
        {
            if (sirf::iequals(flag, "store_prompts"))
                store_prompts = value;
            else if (sirf::iequals(flag, "store_delayeds"))
                store_delayeds = value;
#if 0
            else if (sirf::iequals(flag, "do_pre_normalisation"))
                do_pre_normalisation = value;
            else if (sirf::iequals(flag, "do_time_frame"))
                do_time_frame = value;
#endif
            else if (sirf::iequals(flag, "interactive"))
                interactive = value;
            else
                return -1;
            return 0;
        }
        bool get_store_prompts() const
        {
            return store_prompts;
        }
        bool get_store_delayeds() const
        {
            return store_delayeds;
        }
        virtual stir::Succeeded set_up()
        {
            if (LmToProjData::set_up() == Succeeded::no)
                THROW("LmToProjData setup failed");
            fan_size = -1;
            const int max_fan_size =
                lm_data_ptr->get_scanner_ptr()->get_max_num_non_arccorrected_bins();
            if (fan_size == -1)
                fan_size = max_fan_size;
            else
                fan_size =
                std::min(fan_size, max_fan_size);
            half_fan_size = fan_size / 2;
            fan_size = 2 * half_fan_size + 1;
 
            exam_info_sptr_->set_time_frame_definitions(frame_defs);
            const float h = proj_data_info_sptr_->get_bed_position_horizontal();
            const float v = proj_data_info_sptr_->get_bed_position_vertical();
                        stir::shared_ptr<ProjDataInfo> temp_proj_data_info_sptr(template_proj_data_info_ptr->clone());
            temp_proj_data_info_sptr->set_bed_position_horizontal(h);
            temp_proj_data_info_sptr->set_bed_position_vertical(v);
            randoms_sptr.reset(new STIRAcquisitionDataInMemory(exam_info_sptr_, temp_proj_data_info_sptr));
 
            return stir::Succeeded::yes;
        }
        int estimate_randoms();
        void save_randoms()
        {
            std::string filename = output_filename_prefix + "_randoms" + "_f1g1d0b0.hs";
            randoms_sptr->write(filename.c_str());
        }
        std::shared_ptr<STIRAcquisitionData> get_output()
        {
            std::string filename = output_filename_prefix + "_f1g1d0b0.hs";
            return std::shared_ptr<STIRAcquisitionData>
                (new STIRAcquisitionDataInFile(filename.c_str()));
        }
        std::shared_ptr<STIRAcquisitionData> get_randoms_sptr()
        {
            return randoms_sptr;
        }
        float get_time_at_which_num_prompts_exceeds_threshold(const unsigned long threshold) const;
 
    protected:
        // variables for ML estimation of singles/randoms
        int fan_size;
        int half_fan_size;
        int max_ring_diff_for_fansums;
        int num_iterations;
        int display_interval;
        int KL_interval;
        int save_interval;
        stir::shared_ptr<ExamInfo> exam_info_sptr_;
        stir::shared_ptr<ProjDataInfo> proj_data_info_sptr_;
        stir::shared_ptr<std::vector<stir::Array<2, float> > > fan_sums_sptr;
        stir::shared_ptr<stir::DetectorEfficiencies> det_eff_sptr;
        std::shared_ptr<STIRAcquisitionData> randoms_sptr;
        void compute_fan_sums_(bool prompt_fansum = false);
        int compute_singles_();
//      void estimate_randoms_();
        static unsigned long compute_num_bins_(const int num_rings,
            const int num_detectors_per_ring,
            const int max_ring_diff, const int half_fan_size);
    };
 
    class PETAcquisitionSensitivityModel {
    public:
        PETAcquisitionSensitivityModel() {}
        // create from bin (detector pair) efficiencies sinograms
        PETAcquisitionSensitivityModel(STIRAcquisitionData& ad);
        // create from ECAT8
        PETAcquisitionSensitivityModel(std::string filename);
        // chain two normalizations
        PETAcquisitionSensitivityModel
            (PETAcquisitionSensitivityModel& mod1, PETAcquisitionSensitivityModel& mod2)
        {
            norm_.reset(new stir::ChainedBinNormalisation(mod1.data(), mod2.data()));
        }
 
        void set_up(const stir::shared_ptr<const stir::ExamInfo>& exam_info_sptr,
            const stir::shared_ptr<stir::ProjDataInfo>&);
 
        // multiply by bin efficiencies
        virtual void unnormalise(STIRAcquisitionData& ad) const;
        // divide by bin efficiencies
        virtual void normalise(STIRAcquisitionData& ad) const;
        // same as apply, but returns new data rather than changes old one
        std::shared_ptr<STIRAcquisitionData> forward(const STIRAcquisitionData& ad) const
        {
            std::shared_ptr<STIRAcquisitionData> sptr_ad = ad.new_acquisition_data();
            sptr_ad->fill(ad);
            this->unnormalise(*sptr_ad);
            return sptr_ad;
        }
        // same as undo, but returns new data rather than changes old one
        std::shared_ptr<STIRAcquisitionData> invert(const STIRAcquisitionData& ad) const
        {
            std::shared_ptr<STIRAcquisitionData> sptr_ad = ad.new_acquisition_data();
            sptr_ad->fill(ad);
            this->normalise(*sptr_ad);
            return sptr_ad;
        }
 
        stir::shared_ptr<stir::BinNormalisation> data()
        {
            return norm_;
            //return std::dynamic_pointer_cast<stir::BinNormalisation>(norm_);
        }
 
    protected:
        stir::shared_ptr<stir::BinNormalisation> norm_;
        //shared_ptr<stir::ChainedBinNormalisation> norm_;
    };
 
    
    typedef DataProcessor3DF ImageDataProcessor;
 
    class PETAcquisitionModel {
    public:
        class BFOperator : public Operator<STIRImageData> {
        public:
            BFOperator(const PETAcquisitionModel& am) : sptr_am_(am.linear_acq_mod_sptr()) {}
            void set_subset(int sub_num)
            {
                sub_num_ = sub_num;
            }
            void set_num_subsets(int num_sub)
            {
                num_sub_ = num_sub;
            }
            virtual std::shared_ptr<STIRImageData> apply(const STIRImageData& image_data)
            {
                std::shared_ptr<STIRAcquisitionData> sptr_fwd =
                    sptr_am_->forward(image_data, sub_num_, num_sub_); // , true);
                std::shared_ptr<STIRImageData> sptr_bwd =
                    sptr_am_->backward(*sptr_fwd, sub_num_, num_sub_);
                return sptr_bwd;
            }
        private:
            std::shared_ptr<const PETAcquisitionModel> sptr_am_;
            int sub_num_ = 0;
            int num_sub_ = 1;
        };
 
        float norm(int subset_num = 0, int num_subsets = 1, int num_iter = 2, int verb = 0) const
        {
            BFOperator bf(*this);
            bf.set_subset(subset_num);
            bf.set_num_subsets(num_subsets);
            JacobiCG<float> jcg;
            jcg.set_num_iterations(num_iter);
            STIRImageData image_data = *sptr_image_template_->clone();
            image_data.fill(1.0);
            float lmd = jcg.largest(bf, image_data, verb);
            return std::sqrt(lmd);
        }
 
        void set_projectors(stir::shared_ptr<stir::ProjectorByBinPair> sptr_projectors)
        {
            sptr_projectors_ = sptr_projectors;
        }
        const stir::shared_ptr<stir::ProjectorByBinPair> projectors_sptr() const
        {
            return sptr_projectors_;
        }
        void set_additive_term(std::shared_ptr<STIRAcquisitionData> sptr)
        {
            sptr_add_ = sptr;
        }
        std::shared_ptr<const STIRAcquisitionData> additive_term_sptr() const
        {
            return sptr_add_;
        }
        void set_background_term(std::shared_ptr<STIRAcquisitionData> sptr)
        {
            sptr_background_ = sptr;
        }
        std::shared_ptr<const STIRAcquisitionData> background_term_sptr() const
        {
            return sptr_background_;
        }
        std::shared_ptr<const STIRAcquisitionData> acq_template_sptr() const
        {
            return sptr_acq_template_;
        }
        std::shared_ptr<const STIRImageData> image_template_sptr() const
        {
            return sptr_image_template_;
        }
        //void set_normalisation(shared_ptr<stir::BinNormalisation> sptr)
        //{
        //  sptr_normalisation_ = sptr;
        //}
        const stir::shared_ptr<stir::BinNormalisation> normalisation_sptr() const
        {
            if (sptr_asm_.get())
                return sptr_asm_->data();
            stir::shared_ptr<stir::BinNormalisation> sptr;
            return sptr;
            //return sptr_normalisation_;
        }
        //void set_bin_efficiency(shared_ptr<STIRAcquisitionData> sptr_data);
        //void set_normalisation(shared_ptr<STIRAcquisitionData> sptr_data)
        //{
        //  sptr_normalisation_.reset(new stir::BinNormalisationFromProjData(*sptr_data));
        //}
        void set_asm(std::shared_ptr<PETAcquisitionSensitivityModel> sptr_asm)
        {
            //sptr_normalisation_ = sptr_asm->data();
            sptr_asm_ = sptr_asm;
        }
        stir::shared_ptr<PETAcquisitionSensitivityModel> asm_sptr() const
        {
            return sptr_asm_;
        }
 
 
        void set_image_data_processor(stir::shared_ptr<ImageDataProcessor> sptr_processor);
        void cancel_background_term()
        {
            sptr_background_.reset();
        }
        void cancel_additive_term()
        {
            sptr_add_.reset();
        }
        void cancel_normalisation()
        {
            sptr_asm_.reset();
            //sptr_normalisation_.reset();
        }
        std::shared_ptr<const PETAcquisitionModel> linear_acq_mod_sptr() const
        {
            std::shared_ptr<PETAcquisitionModel> sptr_am(new PETAcquisitionModel);
            sptr_am->set_projectors(sptr_projectors_);
            sptr_am->set_asm(sptr_asm_);
            sptr_am->sptr_acq_template_ = sptr_acq_template_;
            sptr_am->sptr_image_template_ = sptr_image_template_;
            return sptr_am;
        }
 
        virtual void set_up(
            std::shared_ptr<STIRAcquisitionData> sptr_acq,
            std::shared_ptr<STIRImageData> sptr_image);
 
        std::shared_ptr<STIRAcquisitionData>
            forward(const STIRImageData& image,
            int subset_num = 0, int num_subsets = 1, bool do_linear_only = false) const;
        void forward(STIRAcquisitionData& acq_data, const STIRImageData& image,
            int subset_num, int num_subsets, bool zero = false, bool do_linear_only = false) const;
 
        // computes and returns back-projected subset of acquisition data 
        std::shared_ptr<STIRImageData> backward(const STIRAcquisitionData& ad,
            int subset_num = 0, int num_subsets = 1) const;
        // puts back-projected subset of acquisition data into image 
        void backward(STIRImageData& image, const STIRAcquisitionData& ad,
            int subset_num = 0, int num_subsets = 1) const;
 
    protected:
        stir::shared_ptr<stir::ProjectorByBinPair> sptr_projectors_;
        std::shared_ptr<STIRAcquisitionData> sptr_acq_template_;
        std::shared_ptr<STIRImageData> sptr_image_template_;
        std::shared_ptr<STIRAcquisitionData> sptr_add_;
        std::shared_ptr<STIRAcquisitionData> sptr_background_;
        std::shared_ptr<PETAcquisitionSensitivityModel> sptr_asm_;
        //shared_ptr<stir::BinNormalisation> sptr_normalisation_;
    };
 
    class PETSingleScatterSimulator : public stir::SingleScatterSimulation
    {
    public:
        PETSingleScatterSimulator() : stir::SingleScatterSimulation()
        {}
        PETSingleScatterSimulator(std::string filename) :
        stir::SingleScatterSimulation(filename)
        {}
 
        void set_up(std::shared_ptr<const STIRAcquisitionData> sptr_acq_template,
                    std::shared_ptr<const STIRImageData> sptr_act_image_template)
          {
            this->sptr_acq_template_ = sptr_acq_template;
 
            stir::SingleScatterSimulation::set_template_proj_data_info(
                        *sptr_acq_template_->get_proj_data_info_sptr());
            stir::SingleScatterSimulation::set_exam_info(
                        *sptr_acq_template_->get_exam_info_sptr());
            // check if attenuation image is set
            try
              {
                auto& tmp = stir::SingleScatterSimulation::get_attenuation_image();
              }
            catch (...)
              {
                THROW("Fatal error in PETSingleScatterSimulator::set_up: attenuation_image has not been set");
              }
            this->set_activity_image_sptr(sptr_act_image_template);
 
            if (stir::SingleScatterSimulation::set_up() == Succeeded::no)
              THROW("Fatal error in PETSingleScatterSimulator::set_up() failed.");
          }
 
        void set_activity_image_sptr(std::shared_ptr<const STIRImageData> arg)
        {
#if STIR_VERSION < 050000
            // need to make a copy as the function doesn't accept a const
            stir::shared_ptr<Image3DF> sptr_image_copy(arg->data_sptr()->clone());
            stir::SingleScatterSimulation::set_activity_image_sptr(sptr_image_copy);
#else
            stir::SingleScatterSimulation::set_activity_image_sptr(arg->data_sptr());
#endif
        }
 
        void set_attenuation_image_sptr(std::shared_ptr<const STIRImageData> arg)
        {
#if STIR_VERSION < 050000
            // need to make a copy as the function doesn't accept a const
            stir::shared_ptr<Image3DF> sptr_image_copy(arg->data_sptr()->clone());
            stir::SingleScatterSimulation::set_density_image_sptr(sptr_image_copy);
#else
            stir::SingleScatterSimulation::set_density_image_sptr(arg->data_sptr());
#endif
        }
 
        std::shared_ptr<STIRAcquisitionData> forward(const STIRImageData& activity_img) /*TODO CONST*/
          {
            if (!sptr_acq_template_.get())
              THROW("Fatal error in PETSingleScatterSimulator::forward: acquisition template not set");
            std::shared_ptr<STIRAcquisitionData> sptr_ad =
              sptr_acq_template_->new_acquisition_data();
            this->forward( *sptr_ad, activity_img);
            return sptr_ad;
          }
 
        void forward(STIRAcquisitionData& ad, const STIRImageData& activity_img) /* TODO CONST*/
          {
            stir::shared_ptr<ProjData> sptr_fd = ad.data();
            this->set_output_proj_data_sptr(sptr_fd);
            // hopefully STIR checks if template consistent with input data
            this->process_data();
          }
 
    protected:
        std::shared_ptr<const STIRAcquisitionData> sptr_acq_template_;
 
    };
 
    class PETScatterEstimator : private stir::ScatterEstimation
    {
    public:
        PETScatterEstimator() : stir::ScatterEstimation()
        {
          stir::shared_ptr<stir::PoissonLogLikelihoodWithLinearModelForMeanAndProjData<DiscretisedDensity<3,float> > >
            obj_sptr(new PoissonLogLikelihoodWithLinearModelForMeanAndProjData<DiscretisedDensity<3,float> >);
          stir::shared_ptr<stir::OSMAPOSLReconstruction<DiscretisedDensity<3,float> > >
            recon_sptr(new stir::OSMAPOSLReconstruction<DiscretisedDensity<3,float> >);
          recon_sptr->set_num_subiterations(8);
          recon_sptr->set_num_subsets(7); // this works for the mMR. TODO
          recon_sptr->set_disable_output(true);
          recon_sptr->set_objective_function_sptr(obj_sptr);
          stir::shared_ptr<stir::SeparableGaussianImageFilter<float> >
            filter_sptr(new stir::SeparableGaussianImageFilter<float>);
          filter_sptr->set_fwhms(stir::make_coordinate(15.F,15.F,15.F));
          recon_sptr->set_post_processor_sptr(filter_sptr);
          stir::ScatterEstimation::set_reconstruction_method_sptr(recon_sptr);
        }
        PETScatterEstimator(std::string filename) :
        stir::ScatterEstimation(filename)
        {}
 
        void set_input_sptr(std::shared_ptr<const STIRAcquisitionData> arg)
        {
            stir::ScatterEstimation::set_input_proj_data_sptr(arg->data());
        }
        void set_attenuation_correction_factors_sptr(std::shared_ptr<const STIRAcquisitionData> arg)
        {
          stir::ScatterEstimation::set_attenuation_correction_proj_data_sptr(arg->data());
        }
        void set_asm(std::shared_ptr<PETAcquisitionSensitivityModel> arg)
        {
          stir::ScatterEstimation::set_normalisation_sptr(arg->data());
        }
        void set_background_sptr(std::shared_ptr<const STIRAcquisitionData> arg)
        {
            stir::ScatterEstimation::set_background_proj_data_sptr(arg->data());
        }
 
        void set_attenuation_image_sptr(std::shared_ptr<const STIRImageData> arg)
        {
#if STIR_VERSION < 050000
            // need to make a copy as the function doesn't accept a const
            stir::shared_ptr<Image3DF> sptr_image_copy(arg->data_sptr()->clone());
            stir::ScatterEstimation::set_attenuation_image_sptr(sptr_image_copy);
#else
            stir::ScatterEstimation::set_attenuation_image_sptr(arg->data_sptr());
#endif
        }
 
 
        void set_output_prefix(std::string prefix)
        {
          stir::ScatterEstimation::set_export_scatter_estimates_of_each_iteration(!prefix.empty());
          stir::ScatterEstimation::set_output_scatter_estimate_prefix(prefix);
        }
 
        void set_num_iterations(int arg)
        {
          stir::ScatterEstimation::set_num_iterations(arg);
        }
 
        int get_num_iterations() const
        {
          return stir::ScatterEstimation::get_num_iterations();
        }
 
        std::shared_ptr<STIRAcquisitionData> get_scatter_estimate(int est_num = -1) const
        {
            if (est_num == -1) // Get the last one
                est_num = num_scatter_iterations;
            if (est_num == num_scatter_iterations)
              return get_output();
            // try to read from file
            if (output_scatter_estimate_prefix.empty())
              THROW("output_scatter_estimate_prefix not set, so scatter estimates were not saved to file.");
            const std::string filename = output_scatter_estimate_prefix + "_" + std::to_string(est_num) + ".hs";
            return std::make_shared<STIRAcquisitionDataInFile>(filename.c_str());
        }
 
        std::shared_ptr<STIRAcquisitionData> get_output() const
          {
            auto stir_proj_data_sptr = stir::ScatterEstimation::get_output();
            if (!stir_proj_data_sptr)
              THROW("output not yet computed");
            std::shared_ptr<STIRAcquisitionData> sptr_acq_data
              (STIRAcquisitionData::storage_template()->same_acquisition_data(stir_proj_data_sptr->get_exam_info_sptr(),
                                                                             stir_proj_data_sptr->get_proj_data_info_sptr()->create_shared_clone()));
            sptr_acq_data->data()->fill(*stir_proj_data_sptr);
            return sptr_acq_data;
          }
 
 
        Succeeded set_up()
        {
          // reconstruct an smooth image with a large voxel size
          const float zoom = 0.2F;
          stir::shared_ptr<Voxels3DF>
            image_sptr(new Voxels3DF(MAKE_SHARED<stir::ExamInfo>(*this->get_input_data()->get_exam_info_sptr()),
                                     *this->get_input_data()->get_proj_data_info_sptr(),
                                     zoom));
          image_sptr->fill(1.F);
          stir::ScatterEstimation::set_initial_activity_image_sptr(image_sptr);
          if (stir::ScatterEstimation::set_up() == Succeeded::no)
            THROW("scatter estimation set_up failed");
          return Succeeded::yes;
        }
        void process()
        {
          if (!stir::ScatterEstimation::already_setup())
            THROW("scatter estimation needs to be set-up first");
          if (stir::ScatterEstimation::process_data() == Succeeded::no)
            THROW("scatter estimation failed");
        }
    };
 
    class PETAcquisitionModelUsingMatrix : public PETAcquisitionModel {
    public:
        PETAcquisitionModelUsingMatrix()
        {
            this->sptr_projectors_.reset(new ProjectorPairUsingMatrix);
        }
        void set_matrix(stir::shared_ptr<stir::ProjMatrixByBin> sptr_matrix)
        {
            sptr_matrix_ = sptr_matrix;
            ((ProjectorPairUsingMatrix*)this->sptr_projectors_.get())->
                set_proj_matrix_sptr(sptr_matrix);
        }
        stir::shared_ptr<stir::ProjMatrixByBin> matrix_sptr()
        {
            return sptr_matrix_;
            //return ((ProjectorPairUsingMatrix*)this->sptr_projectors_.get())->
            //  get_proj_matrix_sptr();
        }
        virtual void set_up(
            std::shared_ptr<STIRAcquisitionData> sptr_acq,
            std::shared_ptr<STIRImageData> sptr_image)
        {
            if (!sptr_matrix_.get())
                THROW("PETAcquisitionModelUsingMatrix setup failed - matrix not set");
            PETAcquisitionModel::set_up(sptr_acq, sptr_image);
        }
                
                void enable_cache(bool v = true)
                {
                        sptr_matrix_->enable_cache(v);
                }
 
    private:
        stir::shared_ptr<stir::ProjMatrixByBin> sptr_matrix_;
    };
 
    class PETAcquisitionModelUsingRayTracingMatrix :
        public PETAcquisitionModelUsingMatrix {
    public:
        PETAcquisitionModelUsingRayTracingMatrix(int num_LORs = 2) :
            PETAcquisitionModelUsingMatrix()
        {
            stir::shared_ptr<RayTracingMatrix> matrix_sptr(new RayTracingMatrix);
            matrix_sptr->set_num_tangential_LORs(num_LORs);
            set_matrix(matrix_sptr);
        }
        void set_num_tangential_LORs(int num_LORs)
        {
                       //RayTracingMatrix& matrix = (RayTracingMatrix&)*matrix_sptr();
            auto matrix = dynamic_cast<RayTracingMatrix&>(*matrix_sptr());
            //std::cout << matrix.get_num_tangential_LORs() << '\n';
            matrix.set_num_tangential_LORs(num_LORs);
            //std::cout << get_num_tangential_LORs() << '\n';
        }
        int get_num_tangential_LORs()
        {
            auto matrix = dynamic_cast<const RayTracingMatrix&>(*matrix_sptr());
            return matrix.get_num_tangential_LORs();
        }
                void set_restrict_to_cylindrical_FOV(bool v = true)
                {
                        auto matrix = dynamic_cast<RayTracingMatrix&>(*matrix_sptr());
                        matrix.set_restrict_to_cylindrical_FOV(v);
                }
                //bool get_do_symmetry_90degrees_min_phi() const;
                void set_do_symmetry_90degrees_min_phi(bool v = true)
                {
                        auto matrix = dynamic_cast<RayTracingMatrix&>(*matrix_sptr());
                        matrix.set_do_symmetry_90degrees_min_phi(v);
                }
                //bool get_do_symmetry_180degrees_min_phi() const;
                void set_do_symmetry_180degrees_min_phi(bool v = true)
                {
                        auto matrix = dynamic_cast<RayTracingMatrix&>(*matrix_sptr());
                        matrix.set_do_symmetry_180degrees_min_phi(v);
                }
                //bool get_do_symmetry_swap_segment() const;
                void set_do_symmetry_swap_segment(bool v = true)
                {
                        auto matrix = dynamic_cast<RayTracingMatrix&>(*matrix_sptr());
                        matrix.set_do_symmetry_swap_segment(v);
                }
                //bool get_do_symmetry_swap_s() const;
                void set_do_symmetry_swap_s(bool v = true)
                {
                        auto matrix = dynamic_cast<RayTracingMatrix&>(*matrix_sptr());
                        matrix.set_do_symmetry_swap_s(v);
                }
                //bool get_do_symmetry_shift_z() const;
                void set_do_symmetry_shift_z(bool v = true)
                {
                        auto matrix = dynamic_cast<RayTracingMatrix&>(*matrix_sptr());
                        matrix.set_do_symmetry_shift_z(v);
                }
    };
 
    typedef PETAcquisitionModel AcqMod3DF;
    typedef PETAcquisitionModelUsingMatrix AcqModUsingMatrix3DF;
    typedef std::shared_ptr<AcqMod3DF> sptrAcqMod3DF;
 
#ifdef STIR_WITH_NiftyPET_PROJECTOR
    class PETAcquisitionModelUsingNiftyPET : public PETAcquisitionModel {
    public:
        PETAcquisitionModelUsingNiftyPET()
        {
            _NiftyPET_projector_pair_sptr.reset(new ProjectorPairUsingNiftyPET);
            this->sptr_projectors_ = _NiftyPET_projector_pair_sptr;
            // Set verbosity to 0 by default
            _NiftyPET_projector_pair_sptr->set_verbosity(0);
        }
        void set_cuda_verbosity(const bool verbosity) const
        {
            _NiftyPET_projector_pair_sptr->set_verbosity(verbosity);
        }
        void set_use_truncation(const bool use_truncation) const
        {
            _NiftyPET_projector_pair_sptr->set_use_truncation(use_truncation);
        }
    protected:
        stir::shared_ptr<stir::ProjectorPairUsingNiftyPET> _NiftyPET_projector_pair_sptr;
    };
    typedef PETAcquisitionModelUsingNiftyPET AcqModUsingNiftyPET3DF;
#endif
 
#ifdef STIR_WITH_Parallelproj_PROJECTOR
    class PETAcquisitionModelUsingParallelproj : public PETAcquisitionModel {
    public:
        PETAcquisitionModelUsingParallelproj()
        {
            this->sptr_projectors_.reset(new ProjectorByBinPairUsingParallelproj);
        }
    };
    typedef PETAcquisitionModelUsingParallelproj AcqModUsingParallelproj;
#endif
 
    class PETAttenuationModel : public PETAcquisitionSensitivityModel {
    public:
        PETAttenuationModel(STIRImageData& id, PETAcquisitionModel& am);
        // multiply by bin efficiencies
        virtual void unnormalise(STIRAcquisitionData& ad) const;
        // divide by bin efficiencies
        virtual void normalise(STIRAcquisitionData& ad) const;
    protected:
        stir::shared_ptr<stir::ForwardProjectorByBin> sptr_forw_projector_;
    };
 
    class xSTIR_Box3D : public stir::Box3D {
    public:
        void set_length_x(float v)
        {
            length_x = v;
        }
        void set_length_y(float v)
        {
            length_y = v;
        }
        void set_length_z(float v)
        {
            length_z = v;
        }
        float get_length_x() const
        {
            return length_x;
        }
        float get_length_y() const
        {
            return length_y;
        }
        float get_length_z() const
        {
            return length_z;
        }
    };
 
    class xSTIR_GeneralisedPrior3DF : public stir::GeneralisedPrior < Image3DF > {
    public:
//      bool post_process() {
//          return post_processing();
//      }
    };
 
    class xSTIR_QuadraticPrior3DF : public stir::QuadraticPrior < float > {
    public:
        void only2D(int only) {
            only_2D = only != 0;
        }
    };
 
    class xSTIR_LogcoshPrior3DF : public stir::LogcoshPrior < float > {
    public:
        void only2D(int only) {
            only_2D = only != 0;
        }
    };
 
    class xSTIR_RelativeDifferencePrior3DF : public stir::RelativeDifferencePrior < float > {
    public:
        void only2D(int only) {
            only_2D = only != 0;
        }
    };
 
    class xSTIR_PLSPrior3DF : public stir::PLSPrior < float > {
    public:
        void only2D(int only) {
            only_2D = only != 0;
        }
    };
 
    class xSTIR_GeneralisedObjectiveFunction3DF :
        public stir::GeneralisedObjectiveFunction < Image3DF > {
    public:
//      bool post_process() {
//          return post_processing();
//      }
    };
 
    //typedef xSTIR_GeneralisedObjectiveFunction3DF ObjectiveFunction3DF;
 
    class xSTIR_PoissonLogLikelihoodWithLinearModelForMeanAndProjData3DF :
        public stir::PoissonLogLikelihoodWithLinearModelForMeanAndProjData < Image3DF > {
    public:
        void set_input_file(const char* filename) {
            input_filename = filename;
        }
        void set_acquisition_data(std::shared_ptr<STIRAcquisitionData> sptr)
        {
            sptr_ad_ = sptr;
            set_proj_data_sptr(sptr->data());
        }
        void set_acquisition_model(std::shared_ptr<AcqMod3DF> sptr_am)
        {
            sptr_am_ = sptr_am;
            AcqMod3DF& am = *sptr_am;
            auto sptr_asm = am.asm_sptr();
            set_projector_pair_sptr(am.projectors_sptr());
            bool have_a = am.additive_term_sptr().get();
            bool have_b = am.background_term_sptr().get();
            bool have_asm = sptr_asm.get();
            if (!have_b) {
                if (have_a)
                    set_additive_proj_data_sptr(am.additive_term_sptr()->data());
            }
            else {
                auto sptr_b = am.background_term_sptr();
                stir::shared_ptr<STIRAcquisitionData> sptr;
                if (have_asm)
                    sptr = sptr_asm->invert(*sptr_b);
                else
                    sptr = sptr_b->clone();
                if (have_a) {
                    auto sptr_a = am.additive_term_sptr();
                    float a = 1.0f;
                    sptr->axpby(&a, *sptr, &a, *sptr_a);
                }
                set_additive_proj_data_sptr(sptr->data());
            }
            if (am.normalisation_sptr().get())
                set_normalisation_sptr(am.normalisation_sptr());
        }
        std::shared_ptr<AcqMod3DF> acquisition_model_sptr()
        {
            return sptr_am_;
        }
    private:
        std::shared_ptr<STIRAcquisitionData> sptr_ad_;
        std::shared_ptr<AcqMod3DF> sptr_am_;
    };
 
    typedef xSTIR_PoissonLogLikelihoodWithLinearModelForMeanAndProjData3DF
        PoissonLogLhLinModMeanProjData3DF;
 
    class xSTIR_IterativeReconstruction3DF :
        public stir::IterativeReconstruction < Image3DF > {
    public:
/*      bool post_process() {
            //std::cout << "in xSTIR_IterativeReconstruction3DF.post_process...\n";
            if (this->output_filename_prefix.length() < 1)
                this->set_output_filename_prefix("reconstructed_image");
            return post_processing();
        }*/
        void update(Image3DF &image) {
            update_estimate(image);
            end_of_iteration_processing(image);
            subiteration_num++;
        }
        void update(STIRImageData& id)
        {
            update(id.data());
        }
        void update(stir::shared_ptr<STIRImageData> sptr_id)
        {
            update(*sptr_id);
        }
        int& subiteration() {
            return subiteration_num;
        }
        int subiteration() const {
            return subiteration_num;
        }
        void set_initial_estimate_file(const char* filename) {
            initial_data_filename = filename;
        }
    };
 
    class xSTIR_OSMAPOSLReconstruction3DF : public stir::OSMAPOSLReconstruction< Image3DF > {
    public:
        int& subiteration() {
            return subiteration_num;
        }
        int subiteration() const {
            return subiteration_num;
        }
    };
 
    class xSTIR_KOSMAPOSLReconstruction3DF : public stir::KOSMAPOSLReconstruction< Image3DF > {
    public:
        void compute_kernelised_image_x(
                         Image3DF& kernelised_image_out,
                         const Image3DF& image_to_kernelise,
                         const Image3DF& current_alpha_estimate)
        {
            compute_kernelised_image(
                kernelised_image_out,
                image_to_kernelise,
                current_alpha_estimate);
        }
    };
 
    class xSTIR_OSSPSReconstruction3DF : public stir::OSSPSReconstruction < Image3DF > {
    public:
        float& relaxation_parameter_value() {
            return relaxation_parameter;
        }
    };
 
    class xSTIR_FBP2DReconstruction : public stir::FBP2DReconstruction {
    public:
        xSTIR_FBP2DReconstruction()
        {
            _is_set_up = false;
        }
        void set_input(const STIRAcquisitionData& acq)
        {
            set_input_data(acq.data());
        }
        void set_zoom(float v)
        {
            set_zoom_xy(v);
            _is_set_up = false;
        }
        void set_alpha_ramp(double alpha)
        {
            // does not work!
            //assert(alpha > 0 && alpha <= 1.0);
            if (!(alpha > 0 && alpha <= 1.0))
                throw LocalisedException
                ("wrong ramp filter parameter alpha", __FILE__, __LINE__);
            alpha_ramp = alpha;
        }
        void set_frequency_cut_off(double fc)
        {
            if (!(fc > 0 && fc <= 0.5))
                throw LocalisedException
                ("wrong frequency cut-off", __FILE__, __LINE__);
            fc_ramp = fc;
        }
        void set_up(std::shared_ptr<STIRImageData> sptr_id)
        {
            _sptr_image_data.reset(new STIRImageData(*sptr_id));
            stir::Succeeded s = stir::Reconstruction<Image3DF>::set_up(_sptr_image_data->data_sptr());
            if (s != stir::Succeeded::yes)
                THROW("stir::Reconstruction setup failed");
            _is_set_up = true;
        }
        void cancel_setup()
        {
            _is_set_up = false;
        }
        void process()
        {
            stir::Succeeded s = stir::Succeeded::no;
            if (!_is_set_up) {
                stir::shared_ptr<Image3DF> sptr_image(construct_target_image_ptr());
                _sptr_image_data.reset(new STIRImageData(sptr_image));
                stir::Reconstruction<Image3DF>::set_up(sptr_image);
                s = reconstruct(sptr_image);
            }
            else
                s = reconstruct(_sptr_image_data->data_sptr());
            if (s != stir::Succeeded::yes)
                THROW("stir::AnalyticReconstruction::reconstruct failed");
        }
        std::shared_ptr<STIRImageData> get_output()
        {
            return _sptr_image_data;
        }
    protected:
        bool _is_set_up;
        std::shared_ptr<STIRImageData> _sptr_image_data;
    };
 
    class xSTIR_SeparableGaussianImageFilter : 
        public stir::SeparableGaussianImageFilter<float> {
    public:
        //stir::Succeeded set_up(const STIRImageData& id)
        //{
        //  return virtual_set_up(id.data());
        //}
        //void apply(STIRImageData& id)
        //{
        //  virtual_apply(id.data());
        //}
        void set_fwhms_xyz(char xyz, float f)
        {
            stir::BasicCoordinate<3, float> v = get_fwhms();
            switch (xyz) {
            case 'z':
                v[1] = f;
                break;
            case 'y':
                v[2] = f;
                break;
            case 'x':
                v[3] = f;
            }
            set_fwhms(v);
        }
        void set_max_kernel_sizes_xyz(char xyz, int s)
        {
            stir::BasicCoordinate<3, int> v = get_max_kernel_sizes();
            switch (xyz) {
            case 'z':
                v[1] = s;
                break;
            case 'y':
                v[2] = s;
                break;
            case 'x':
                v[3] = s;
            }
            set_max_kernel_sizes(v);
        }
    };
}
 
#endif