void LoadFiles(int argc, char* argv[]) {
itkcmds::itkImageIO<ImageType> io;
itkcmds::itkImageIO<LabelType> io2;
_src = io.ReadImageT(argv[1]);
_dst = io.ReadImageT(argv[2]);
_dstLabel = io2.ReadImageT(argv[3]);
_transformOut = argv[4];
_resampledOut = argv[5];
cout << "Transform Output: " << _transformOut << endl;
cout << "Resampled Output: " << _resampledOut << endl;
ImageType::SizeType szDst = _dst->GetBufferedRegion().GetSize();
itk::ContinuousIndex<double,3> szIdx;
for (int i = 0; i < 3; i++) {
szIdx[i] = szDst[i] / 2.0;
}
_dst->TransformContinuousIndexToPhysicalPoint(szIdx, _dstCenter);
itk::ImageRegionConstIteratorWithIndex<LabelType> labelIter(_dstLabel, _dstLabel->GetBufferedRegion());
for (labelIter.GoToBegin(); !labelIter.IsAtEnd(); ++labelIter) {
LabelType::PixelType label = labelIter.Get();
if (label > 0) {
_labelIndexes.push_back(labelIter.GetIndex());
}
}
_centerOfRotation.SetSize(ImageType::ImageDimension);
for (int i = 0; i < 3; i++) {
_centerOfRotation[i] = _dstCenter[i];
}
}
// ------------------------------------------------------------------------
void computeProbImage(const PatchParams ¶ms, unsigned int pnum,
unsigned int id, std::string type, ClassifierMap &classifiers,
const ValveType::Pointer &valve, const LabelType::Pointer &mask, RealImageType::Pointer &output)
{
output = RealImageType::New();
output->SetDirection(mask->GetDirection());
output->SetSpacing(mask->GetSpacing());
output->SetOrigin(mask->GetOrigin());
output->SetRegions(mask->GetLargestPossibleRegion());
output->Allocate();
output->FillBuffer(0);
itk::ImageRegionIterator<LabelType> maskIt(mask, mask->GetLargestPossibleRegion());
itk::ImageRegionIterator<RealImageType> probIt(output, output->GetLargestPossibleRegion());
unsigned int count = 0;
while(!maskIt.IsAtEnd())
{
if(maskIt.Get() == 255)
{
IndexType index = maskIt.GetIndex();
PointType point;
output->TransformIndexToPhysicalPoint(index, point);
MatrixType feature;
extractLBPFeature(params, valve, point, feature);
MatrixType probs;
IntMatrixType classes;
classifiers["MV-"+type][pnum]->PredictProbability(feature, classes, probs);
probIt.Set(probs(0,1));
count++;
}
++maskIt;
++probIt;
}
}
// ------------------------------------------------------------------------
void FlipImage(const LabelType::Pointer &input, LabelType::Pointer &output)
{
if(!output) output = LabelType::New();
ImageType::DirectionType outputDirection = input->GetDirection();
typedef itk::PermuteAxesImageFilter<LabelType> FlipperType;
FlipperType::PermuteOrderArrayType axes;
axes[0] = 1;
axes[1] = 0;
axes[2] = 2;
FlipperType::Pointer flipper = FlipperType::New();
flipper->SetInput(input);
flipper->SetOrder(axes);
flipper->Update();
output = flipper->GetOutput();
output->SetDirection(outputDirection);
}
int main(int argc, char* argv[])
{
//if(argc < 5){
// std::cout<<"Usage1: darpa_tracer <Global_Centroids_List> <DAPI_Montage_File> <GFP_Montage_File> <Seg_Params_File> \n";
// return 0;
//}
//Input: Somas_file, nucleus_montage, trace_channel_montage, nuc_seg_parameters
//std::fstream soma_centroid_file;
//soma_centroid_file.open(argv[1], std::fstream::in);
//std::vector<centroids> centroid_list;
//while (soma_centroid_file.good()){
// centroids new_centroid;
// soma_centroid_file >> new_centroid.x_d >> new_centroid.y_d >> new_centroid.z_d;
// centroid_list.push_back( new_centroid );
//}
//soma_centroid_file.close();
std::vector< itk::Index<3> > centroid_list;
std::vector< itk::Index<3> > all_centroid_list;
//vtkSmartPointer<vtkTable> global_centroids = ftk::LoadTable(argv[1]);
vtkSmartPointer<vtkTable> global_centroids = ftk::LoadTable("D:\\11_10_selective_tracing\\Global_centroids.txt");
for(int r=0; r<(int)global_centroids->GetNumberOfRows(); ++r)
{
int cx = global_centroids->GetValue(r, 0).ToInt();
int cy = global_centroids->GetValue(r, 1).ToInt();
int cz = global_centroids->GetValue(r, 2).ToInt();
itk::Index<3> all_cen;
all_cen[0] = cx; all_cen[1] = cy; all_cen[2] = cz;
all_centroid_list.push_back(all_cen);
if( (fmod((double)cx,1050)>1000) || (fmod((double)cx,1050)<50) || (fmod((double)cy,1050)>1000) || (fmod((double)cy,1050)<50))
{
itk::Index<3> cen;
cen[0] = cx; cen[1] = cy; cen[2] = cz;
centroid_list.push_back(cen);
}
}
std::cout << "Number of cells to be retraced : " << centroid_list.size() << "\n";
typedef itk::ImageFileReader<nucImageType> nucReaderType;
typedef itk::ImageFileReader<gfpImageType> gfpReaderType;
//nucReaderType::Pointer reader_nuc = nucReaderType::New();
//reader_nuc->SetFileName(argv[2]);
//reader_nuc->Update();
//nucImageType::Pointer img_nuc = reader_nuc->GetOutput();
//gfpReaderType::Pointer reader_trace = gfpReaderType::New();
//reader_trace->SetFileName(argv[3]);
//reader_trace->Update();
//gfpImageType::Pointer img_trace = reader_trace->GetOutput();
//uint64_t size_trace[3],size_nuc[3];
//size_nuc[0] = img_nuc->GetLargestPossibleRegion().GetSize()[0];
//size_nuc[1] = img_nuc->GetLargestPossibleRegion().GetSize()[1];
//size_nuc[2] = img_nuc->GetLargestPossibleRegion().GetSize()[2];
//size_trace[0] = img_trace->GetLargestPossibleRegion().GetSize()[0];
//size_trace[1] = img_trace->GetLargestPossibleRegion().GetSize()[1];
//size_trace[2] = img_trace->GetLargestPossibleRegion().GetSize()[2];
//if( size_trace[0]!=size_nuc[0] || size_trace[1]!=size_nuc[1] || size_trace[2]!=size_nuc[2] ) return EXIT_FAILURE;
// //long int a=0;
// //while( a<centroid_list.size() ){
// #pragma omp parallel for num_threads(12)
// for( long int a=0; a<centroid_list.size(); ++a ){
// //for( long int a=0; a<5; ++a ){
// int x, y, z;
// x = centroid_list[a][0];
// y = centroid_list[a][1];
// z = centroid_list[a][2];
//
// nucImageType::IndexType start;
// start[0] = ((x - 200)>0) ? (x - 200):0;
// start[1] = ((y - 200)>0) ? (y - 200):0;
// start[2] = ((z - 100) >0) ? (z - 100) :0;
//
// gfpImageType::IndexType start2;
// start2[0] = ((x - 200)>0) ? (x - 200):0;
// start2[1] = ((y - 200)>0) ? (y - 200):0;
// start2[2] = ((z - 100) >0) ? (z - 100) :0;
//
// nucImageType::SizeType size;
// size[0] = ((x+200)<size_nuc[0]) ? 400 : (200+size_trace[0]-x-1);
// size[1] = ((y+200)<size_nuc[1]) ? 400 : (200+size_trace[1]-y-1);
// size[2] = ((z+100)<size_nuc[2]) ? 200 : (100+size_trace[2]-z-1);
//
// gfpImageType::SizeType size2;
// size2[0] = ((x+200)<size_trace[0]) ? 400 : (200+size_trace[0]-x-1);
// size2[1] = ((y+200)<size_trace[1]) ? 400 : (200+size_trace[1]-y-1);
// size2[2] = ((z+100)<size_trace[2]) ? 200 : (100+size_trace[2]-z-1);
//
// std::ostringstream output_filename_stream;
//
// nucImageType::RegionType desiredRegion;
// desiredRegion.SetSize(size);
// desiredRegion.SetIndex(start);
//
// gfpImageType::RegionType desiredRegion2;
// desiredRegion2.SetSize(size2);
// desiredRegion2.SetIndex(start2);
//
// typedef itk::RegionOfInterestImageFilter< nucImageType, nucImageType > ROIFilterType;
// typedef itk::RegionOfInterestImageFilter< gfpImageType, gfpImageType > ROIFilterType2;
// ROIFilterType::Pointer ROIfilter = ROIFilterType::New();
// ROIfilter->SetRegionOfInterest(desiredRegion);
// ROIfilter->SetInput(img_nuc);
// ROIfilter->Update();
// nucImageType::Pointer img = ROIfilter->GetOutput();
//
// ROIFilterType2::Pointer ROIfilter2 = ROIFilterType2::New();
// ROIfilter2->SetRegionOfInterest(desiredRegion2);
// ROIfilter2->SetInput(img_trace);
// ROIfilter2->Update();
// gfpImageType::Pointer img_tr = ROIfilter2->GetOutput();
//
// //itk::CastImageFilter<gfpImageType, nucImageType>::Pointer caster = itk::CastImageFilter<gfpImageType, nucImageType>::New();
// //caster->SetInput(img_tr);
// //itk::ImageFileWriter<nucImageType>::Pointer writer2 = itk::ImageFileWriter<nucImageType>::New();
// itk::ImageFileWriter<gfpImageType>::Pointer writer2 = itk::ImageFileWriter<gfpImageType>::New();
// std::stringstream ss;
// ss << "gfp_image" << x << "_" << y << "_" << z << ".mhd";
// std::string file_output;
// file_output = ss.str();
// writer2->SetFileName(file_output.c_str());
// writer2->SetInput(img_tr);
// writer2->Update();
//
// //Run Nucleus Segmentation
// clock_t startTimer = clock();
// std::cout<<"Starting segmentation\n";
// unsigned char *in_Image;
// in_Image = (unsigned char *) malloc (size[0]*size[1]*size[2]);
// if( in_Image == NULL ){
// std::cerr<<"Nucleus Seg failed because malloc failed\n";
// continue;
// }
// memset(in_Image/*destination*/,0/*value*/,size[0]*size[1]*size[2]*sizeof(unsigned char)/*num bytes to move*/);
// typedef itk::ImageRegionConstIterator< nucImageType > ConstIteratorType;
// ConstIteratorType pix_buf( img, img->GetRequestedRegion() );
// uint64_t ind=0;
// for ( pix_buf.GoToBegin(); !pix_buf.IsAtEnd(); ++pix_buf, ++ind )
// in_Image[ind]=(pix_buf.Get());
// yousef_nucleus_seg *NucleusSeg = new yousef_nucleus_seg();
// NucleusSeg->readParametersFromFile(argv[4]);
// NucleusSeg->setDataImage(in_Image,size[0],size[1],size[2],"/home/gramak/Desktop/11_10_tracing/montage_kt11306_w410DAPIdsu.mhd");
// NucleusSeg->runBinarization();
// try
// {
// std::cout<<"Starting seed detection\n";
// NucleusSeg->runSeedDetection();
// }
// catch( bad_alloc & excp )
// {
// std::cout<<"You have requested more memory than "
// <<"what is currently available in this "
// <<"system, please try again with a smaller "
// <<"input image\n";
// }
// catch( itk::ExceptionObject & excp )
// {
// std::cout<<"Error: " << excp <<std::endl;
// }
// NucleusSeg->runClustering();
// unsigned short *output_img;
///* if(NucleusSeg->isSegmentationFinEnabled())
// {
// NucleusSeg->runAlphaExpansion();
// output_img=NucleusSeg->getSegImage();
// }
// else
//*/
// output_img=NucleusSeg->getClustImage();
// std::cout<<"Done with nucleus segmentation for image "<<a<<std::endl;
//
// LabelType::Pointer image = LabelType::New();
// LabelType::PointType origin;
// origin[0] = start[0]; //Is this OK?
// origin[1] = start[1];
// origin[2] = start[2];
// image->SetOrigin( origin );
// LabelType::IndexType start1;
// start1[0] = 0;
// start1[1] = 0;
// start1[2] = 0;
// LabelType::SizeType size1;
// size1[0] = size[0];
// size1[1] = size[1];
// size1[2] = size[2];
// LabelType::RegionType region;
// region.SetSize ( size1 );
// region.SetIndex( start1 );
// image->SetRegions( region );
// image->Allocate();
// image->FillBuffer(0);
// image->Update();
//
// typedef itk::ImageRegionIteratorWithIndex< LabelType > IteratorType;
// IteratorType iterator1(image,image->GetRequestedRegion());
// for(uint64_t i=0; i<(size[0]*size[1]*size[2]); ++i)
// {
// unsigned short val = (unsigned short)output_img[i];
// iterator1.Set(val);
// ++iterator1;
// }
//
// std::stringstream ss1;
// ss1 << "soma_label"<< x << "_" << y << "_" << z << ".tif";
// std::string file_output1;
// file_output1 = ss1.str();
// itk::ImageFileWriter<LabelType>::Pointer writer = itk::ImageFileWriter<LabelType>::New();
// writer->SetFileName(file_output1);
// writer->SetInput(image);
// writer->Update();
// delete NucleusSeg;
// }
long int a=0;
int num_to_be_traced = centroid_list.size();
std::cout << "Deleting duplicated seeds.... \n";
while( a<centroid_list.size() )
{
//Run Multiple Neuron Tracer
int x, y, z;
x = centroid_list[a][0];
y = centroid_list[a][1];
z = centroid_list[a][2];
if(x == -1)
{
++a;
continue;
}
itk::Index<3> centroid;
centroid[0] = ((x - 200)>0) ? 200:x;
centroid[1] = ((y - 200)>0) ? 200:y;
centroid[2] = ((z - 100) >0) ? 100:z;
std::stringstream ss1;
ss1 << "D:\\11_10_selective_tracing\\soma_label"<< centroid_list.at(a)[0] << "_" << centroid_list.at(a)[1] << "_" << centroid_list.at(a)[2] << ".tif";
std::string file_output1;
file_output1 = ss1.str();
itk::ImageFileReader<LabelType>::Pointer reader = itk::ImageFileReader<LabelType>::New();
reader->SetFileName(file_output1);
reader->Update();
LabelType::Pointer image = reader->GetOutput();
std::cout << image->GetBufferedRegion().GetSize() << "\n";
typedef itk::ImageRegionIteratorWithIndex< LabelType > IteratorType;
IteratorType iterator1(image,image->GetRequestedRegion());
std::vector< itk::Index<3> > soma_centroids;
std::vector< itk::Index<3> > soma_centroids_to_be_del;
std::vector<unsigned short> label_vec;
std::vector<uint64_t> delete_index;
for(uint64_t ctr =0; ctr<all_centroid_list.size() ; ++ctr)
{
itk::Index<3> cen = all_centroid_list[ctr];
if(cen[0] == -1) continue;
if(abs((double)(cen[0]-x))<200 && abs((double)(cen[1]-y))<200 && abs((double)(cen[2]-z))<100 )
{
bool centroid_not_found = true;
itk::Index<3> centroid2;
centroid2[0] = centroid[0] + cen[0] - x;
centroid2[1] = centroid[1] + cen[1] - y;
centroid2[2] = centroid[2] + cen[2] - z;
LabelType::IndexType centroid_index;
centroid_index[0] = centroid2[0]; centroid_index[1] = centroid2[1]; centroid_index[2] = centroid2[2];
iterator1.SetIndex( centroid_index );
unsigned short centroid_label = iterator1.Get();
for(int b=0; b<label_vec.size(); ++b)
{
if( label_vec.at(b)==centroid_label )
{
centroid_not_found = false;
break;
}
}
if( centroid_not_found )
{
label_vec.push_back( centroid_label );
soma_centroids.push_back( centroid2 );
}
if( !centroid_not_found )
{
delete_index.push_back( ctr );
soma_centroids_to_be_del.push_back( cen );
}
}
}
if( delete_index.size() )
{
std::sort(delete_index.begin(), delete_index.end(), myfunction);
for( uint64_t b=0; b<delete_index.size(); ++b )
all_centroid_list[delete_index[b]].Fill(-1);
delete_index.clear();
for( uint64_t b=0; b<soma_centroids_to_be_del.size(); ++b )
{
itk::Index<3> centroid2 = soma_centroids_to_be_del.at(b);
for( uint64_t c=0; c<centroid_list.size(); ++c )
{
itk::Index<3> centroid3 = centroid_list.at(c);
if( centroid2[0]==centroid3[0] && centroid2[1]==centroid3[1] && centroid2[2]==centroid3[2] )
{
delete_index.push_back( c );
break;
}
}
}
std::sort(delete_index.begin(), delete_index.end(), myfunction);
for( uint64_t b=0; b<delete_index.size(); ++b )
{
centroid_list[delete_index[b]].Fill(-1);
--num_to_be_traced;
}
std::cout<<"Number of cells to be retraced : "<<num_to_be_traced << " after "<<a<<" processed\n";
}
++a;
}
std::cout << "Deleting duplicated seeds done !! \n";
//std::ostringstream swc_filename_stream;
//swc_filename_stream << vul_file::strip_extension(argv[3]) << "_" << x << "_" << y << "_" << z << "_ANT.swc";
//ofstream outFile;
//outFile.open("D:\\11_10_selective_tracing\\append_to_swc.txt", ios::out | ios::trunc );
//if ( !outFile.is_open() )
//{
// std::cerr << "Failed to Load Document: " << outFile << std::endl;
// return false;
//}
////Write out the features:
//for( a=0; a<centroid_list.size(); ++a )
//{
// int x, y, z;
// x = centroid_list[a][0];
// y = centroid_list[a][1];
// z = centroid_list[a][2];
// if(x == -1) continue;
// std::stringstream ssx, ssy, ssz;
// ssx << x; ssy << y; ssz << z;
// outFile << "_Trace_" + ssx.str() + "_" + ssy.str() + "_" + ssz.str() + "_ANT.swc\n";
//}
//outFile.close();
#pragma omp parallel for num_threads(12)
for( a=0; a<centroid_list.size(); ++a )
{
int x, y, z;
x = centroid_list[a][0];
y = centroid_list[a][1];
z = centroid_list[a][2];
if(x == -1) continue;
std::cout<< "Tracing from seed point " << x << "_" << y << "_" << z << "\n";
itk::Index<3> centroid;
centroid[0] = ((x - 200)>0) ? 200:x;
centroid[1] = ((y - 200)>0) ? 200:y;
centroid[2] = ((z - 100) >0) ? 100:z;
std::stringstream ss1;
ss1 << "D:\\11_10_selective_tracing\\soma_label"<< centroid_list.at(a)[0] << "_" << centroid_list.at(a)[1] << "_" << centroid_list.at(a)[2] << ".tif";
std::string file_output1;
file_output1 = ss1.str();
itk::ImageFileReader<LabelType>::Pointer reader = itk::ImageFileReader<LabelType>::New();
reader->SetFileName(file_output1);
reader->Update();
LabelType::Pointer image = reader->GetOutput();
itk::ImageFileReader<gfpImageType>::Pointer reader2 = itk::ImageFileReader<gfpImageType>::New();
std::stringstream ss;
ss << "D:\\11_10_selective_tracing\\gfp_image" << x << "_" << y << "_" << z << ".mhd";
std::string file_output;
file_output = ss.str();
reader2->SetFileName(file_output.c_str());
reader2->Update();
gfpImageType::Pointer img_tr = reader2->GetOutput();
std::vector< itk::Index<3> > soma_centroids;
for(int ctr =0; ctr<all_centroid_list.size() ; ++ctr)
{
itk::Index<3> cen = all_centroid_list[ctr];
if(cen[0] == -1) continue;
if(abs((double)(cen[0]-x))<=200 && abs((double)(cen[1]-y))<=200 && abs((double)(cen[2]-z))<=100 )
{
itk::Index<3> centroid2;
centroid2[0] = centroid[0] + cen[0] - x; //Is there a reason why x and y are flipped?
centroid2[1] = centroid[1] + cen[1] - y;
centroid2[2] = centroid[2] + cen[2] - z;
soma_centroids.push_back(centroid2);
}
}
MultipleNeuronTracer * MNT = new MultipleNeuronTracer();
MNT->LoadCurvImage_1(img_tr, 1);
MNT->ReadStartPoints_1(soma_centroids, 1);
MNT->SetCostThreshold(600);
MNT->LoadSomaImage_1(image);
MNT->RunTracing();
/*MNT->WriteSWCFile(std::string(swc_filename_stream.str()), 1);*/
std::stringstream ssx, ssy, ssz;
ssx << x; ssy << y; ssz << z;
MNT->WriteSWCFile("D:\\11_10_selective_tracing\\_Trace_" + ssx.str() + "_" + ssy.str() + "_" + ssz.str() + "_ANT.swc", 1);
delete MNT;
}
}
void RunRegistration() {
_transform = TransformType::New();
OptiReporter::Pointer optiReporter = OptiReporter::New();
Metric::Pointer metric = Metric::New();
metric->SetFixedImage(_dst);
bool useIndexes = false;
if (useIndexes) {
_centerOfRotation.SetSize(ImageType::ImageDimension);
for (int i = 0; i < ImageType::ImageDimension; i++) {
_centerOfRotation[i] = i;
}
itk::ImageRegionConstIteratorWithIndex<LabelType> labelIter(_dstLabel, _dstLabel->GetBufferedRegion());
int nPixels = 0;
for (labelIter.GoToBegin(); !labelIter.IsAtEnd(); ++labelIter) {
LabelType::PixelType label = labelIter.Get();
if (label > 0) {
_labelIndexes.push_back(labelIter.GetIndex());
for (int i = 0; i < ImageType::ImageDimension; i++) {
_centerOfRotation[i] += labelIter.GetIndex()[i];
}
nPixels ++;
}
}
for (int i = 0; i < ImageType::ImageDimension; i++) {
_centerOfRotation[i] /= nPixels;
}
metric->SetFixedImageIndexes(_labelIndexes);
_transform->SetFixedParameters(_centerOfRotation);
} else {
metric->SetFixedImageRegion(_dst->GetBufferedRegion());
metric->SetUseAllPixels(true);
_centerOfRotation.SetSize(ImageType::ImageDimension);
for (int i = 0; i < 3; i++) {
_centerOfRotation[i] = _dstCenter[i];
}
_transform->SetFixedParameters(_centerOfRotation);
}
cout << "Fixed Parameters: " << _centerOfRotation << endl;
metric->SetMovingImage(_src);
metric->SetInterpolator(Interpolator::New());
metric->SetTransform(_transform);
metric->Initialize();
Optimizer::Pointer opti = Optimizer::New();
opti->SetCostFunction(metric);
Optimizer::ScalesType scales;
scales.SetSize(TransformType::ParametersDimension);
scales.Fill(1);
if (_method == "affine") {
cout << "apply affine scaling ..." << endl;
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 3; j++) {
if (i == j) {
scales[3*i+j] = 160;
} else {
scales[3*i+j] = 30;
}
}
}
scales[9] = scales[10] = scales[11] = 0.1;
} else if (_method == "scale") {
scales[0] = scales[1] = scales[2] = 30;
scales[3] = scales[4] = scales[5] = .5;
scales[6] = scales[7] = scales[8] = 100;
} else if (_method == "similar") {
scales[0] = scales[1] = scales[2] = 10;
scales[3] = scales[4] = scales[5] = 0.5;
scales[6] = 100;
}
opti->SetScales(scales);
const int maxIters = 100;
#ifdef USE_CG_OPTIMIZER
opti->SetMaximumIteration(maxIters);
opti->SetMaximumLineIteration(10);
opti->SetUseUnitLengthGradient(true);
opti->SetStepLength(1);
opti->SetToFletchReeves();
#endif
#ifdef USE_GD_OPTIMIZER
opti->SetNumberOfIterations(maxIters);
opti->SetMinimumStepLength(1e-4);
opti->SetMaximumStepLength(3);
opti->SetRelaxationFactor(.5);
opti->SetGradientMagnitudeTolerance(1e-4);
#endif
opti->SetInitialPosition(_transform->GetParameters());
opti->AddObserver(itk::StartEvent(), optiReporter);
opti->AddObserver(itk::IterationEvent(), optiReporter);
opti->StartOptimization();
cout << "Current Cost: " << opti->GetValue() << endl;
_transformResult = opti->GetCurrentPosition();
_transform->SetParameters(opti->GetCurrentPosition());
}