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/*
This file implements some utility functions
Hongzhi Wang 07/19/2010
*/
#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkRescaleIntensityImageFilter.h"
#include "itkConstNeighborhoodIterator.h"
#include "itkImageRegionIterator.h"
#include "itkImageIterator.h"
#include "itkBinaryErodeImageFilter.h"
#include "itkBinaryDilateImageFilter.h"
#include "itkBinaryBallStructuringElement.h"
#include "itkImageLinearConstIteratorWithIndex.h"
#include "itkImageLinearIteratorWithIndex.h"
#include "itkBinaryThresholdImageFilter.h"
#include <stdio.h>
#include <vector>
#include <string>
#include <cmath>
#include <algorithm>
using namespace std;
namespace
{
const unsigned int Dimension = 3;
typedef float PixelType;
typedef itk::Image< PixelType, Dimension > ImageType;
typedef itk::ImageFileReader< ImageType > ReaderType;
typedef itk::ImageFileWriter< ImageType > WriterType;
typedef float WritePixelType;
typedef itk::Image< WritePixelType, Dimension > WriteImageType;
typedef itk::ImageLinearConstIteratorWithIndex< ImageType > ConstIteratorType;
typedef itk::NeighborhoodIterator< ImageType > NeighborhoodIteratorType;
typedef itk::ImageRegionIteratorWithIndex< ImageType > IndexIteratorType;
typedef itk::ImageRegionIterator< ImageType> IteratorType;
typedef ImageType::RegionType RegionType;
typedef itk::Image<float, Dimension> PosteriorImage;
typedef PosteriorImage::Pointer PosteriorImagePtr;
typedef std::map<float, PosteriorImagePtr> PosteriorMap;
}
// perform thresholding and dilation to obtain region of interest for some segmentation label
// im: input image
// dmask: the resulting region of interest mask. Value 0 represents background, 1 is the ROI.
// Tlabel: specifies the label of interst. If Tlabel<0, then all non-background labels are used.
// R: specifies the dilation radius.
void myDilate(ImageType::Pointer im, ImageType::Pointer dmask, int Tlabel, int R){
int x, y, z, j, k, l;
ImageType::IndexType idx;
ImageType::Pointer tmask = ImageType::New();
tmask->SetRegions(im->GetRequestedRegion());
tmask->SetSpacing(im->GetSpacing() );
tmask->SetOrigin(im->GetOrigin() );
tmask->SetDirection(im->GetDirection());
tmask->Allocate();
int Dx=im->GetRequestedRegion().GetSize()[0];
int Dy=im->GetRequestedRegion().GetSize()[1];
int Dz=im->GetRequestedRegion().GetSize()[2];
IndexIteratorType dmaskit(dmask, dmask->GetRequestedRegion());
IndexIteratorType tmaskit(tmask, tmask->GetRequestedRegion());
IndexIteratorType imit(im, im->GetRequestedRegion());
for (dmaskit.GoToBegin(),tmaskit.GoToBegin(); !dmaskit.IsAtEnd(); ++dmaskit,++tmaskit){
dmaskit.Set(0);
tmaskit.Set(0);
}
int tc=0;
for (imit.GoToBegin(); !imit.IsAtEnd(); ++imit){
idx = imit.GetIndex();
if ((Tlabel>=0 && imit.Value()==Tlabel) || (Tlabel<0 && imit.Value()>0)){
tc++;
x=idx[0];
for (j=-R;j<R+1;j++){
idx[0] = x+j;
if (idx[0]<0 || idx[0]>=Dx)
continue;
dmaskit.SetIndex(idx);
dmaskit.Set(1);
}
}
}
// cout<<"tc: "<<tc<<endl;
for (dmaskit.GoToBegin(); !dmaskit.IsAtEnd(); ++dmaskit){
idx = dmaskit.GetIndex();
if (dmaskit.Value()==1){
y=idx[1];
for (k=-R;k<R+1;k++){
idx[1] = y+k;
if (idx[1]<0 || idx[1]>=Dy)
continue;
tmaskit.SetIndex(idx);
tmaskit.Set(1);
}
}
}
for (tmaskit.GoToBegin(); !tmaskit.IsAtEnd(); ++tmaskit){
idx = tmaskit.GetIndex();
if (tmaskit.Value()==1){
z=idx[2];
for (l=-R;l<R+1;l++){
idx[2] = z+l;
if (idx[2]<0 || idx[2]>=Dz)
continue;
dmaskit.SetIndex(idx);
dmaskit.Set(1);
}
}
}
}
// This function applies MRF optimization.
// ICM (Besag 1986, http://www.stat.duke.edu/~scs/Courses/Stat376/Papers/GibbsFieldEst/BesagDirtyPicsJRSSB1986.pdf)
// Originally implemented by Paul for the c3d software. Adopted by Hongzhi for segadapter.
void MRF_ICM(ImageType::Pointer nseg, PosteriorMap m_PosteriorMap, int ML, vector<int> labelset, double beta, int niter)
{
// Allocate array for neighborhood histogram
double *nhist = new double[ML+1];
// Define an inner region (no boundary voxels)
RegionType r_inner = nseg->GetBufferedRegion();
for(size_t d = 0; d < 3; d++)
{
r_inner.SetIndex(d, r_inner.GetIndex(d)+1);
r_inner.SetSize(d, r_inner.GetSize(d)-2);
}
// Create neighborhood iterator
typedef itk::NeighborhoodIterator<ImageType> NeighborIterType;
NeighborIterType::RadiusType radius;
radius.Fill(1);
NeighborIterType nit(radius, nseg, r_inner);
nit.SetNeedToUseBoundaryCondition(false);
// Do some iterations
for(int q = 0; q < niter; q++)
{
cout<<"iter: "<<q<<endl;
// Keep track of number of updates
size_t n_upd = 0;
// Iterate over the inner region
IndexIteratorType rit(nseg, r_inner);
for(rit.GoToBegin(); !rit.IsAtEnd(); ++rit)
{
// Current pixel value
PixelType x_i = rit.Value();
// Clear the neighborhood histogram
for(int j = 0; j < ML; j++)
nhist[j] = 0.0;
// Make up for the fact that the current voxel will be counted
nhist[(int)x_i] = -1;
// Iterate the neighborhood
nit.SetLocation(rit.GetIndex()); // Slow , change later
for(size_t k = 0; k < nit.Size(); k++)
nhist[(int)nit.GetPixel(k)]++;
// For each candidate label value, compute conditional posterior
int j_best = (int)x_i;
double post_best = 1e100;
for(size_t j = 0; j < labelset.size(); j++)
{
int label=labelset[j];
double p = m_PosteriorMap[label]->GetPixel(rit.GetIndex());
if(p > 0)
{
double likelihood = -log(p);
double prior = - beta * nhist[label];
double post = likelihood + prior;
if(post_best > post)
{
post_best = post;
j_best=label;
}
}
}
if(x_i != j_best)
{
rit.Set(j_best);
n_upd++;
}
}
cout<<n_upd<<" voxels modified."<<endl;
if(n_upd == 0)
{
cout << " Early convergence after " << q << " iterations" << endl;
break;
}
}
cout<<"MRF optimization is finished."<<endl;
delete[] nhist;
}
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