1 /*=========================================================================
2 Program: vv http://www.creatis.insa-lyon.fr/rio/vv
5 - University of LYON http://www.universite-lyon.fr/
6 - Léon Bérard cancer center http://oncora1.lyon.fnclcc.fr
7 - CREATIS CNRS laboratory http://www.creatis.insa-lyon.fr
9 This software is distributed WITHOUT ANY WARRANTY; without even
10 the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
11 PURPOSE. See the copyright notices for more information.
13 It is distributed under dual licence
15 - BSD See included LICENSE.txt file
16 - CeCILL-B http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html
17 ======================================================================-====*/
20 #include "clitkCommon.h"
24 #include "itkImageFileReader.h"
25 #include "itkImageSeriesReader.h"
26 #include "itkImageFileWriter.h"
27 #include "itkRecursiveGaussianImageFilter.h"
28 #include "itkResampleImageFilter.h"
29 #include "itkAffineTransform.h"
30 #include "itkNearestNeighborInterpolateImageFunction.h"
31 #include "itkLinearInterpolateImageFunction.h"
32 #include "itkBSplineInterpolateImageFunction.h"
33 #include "itkBSplineInterpolateImageFunctionWithLUT.h"
34 #include "itkCommand.h"
36 //--------------------------------------------------------------------
37 template <class TInputImage, class TOutputImage>
38 clitk::ResampleImageWithOptionsFilter<TInputImage, TOutputImage>::
39 ResampleImageWithOptionsFilter():itk::ImageToImageFilter<TInputImage, TOutputImage>()
41 static const unsigned int dim = InputImageType::ImageDimension;
42 this->SetNumberOfRequiredInputs(1);
43 m_OutputIsoSpacing = -1;
44 m_InterpolationType = NearestNeighbor;
45 m_GaussianFilteringEnabled = true;
47 m_BLUTSamplingFactor = 20;
48 m_LastDimensionIsTime = false;
49 m_Transform = TransformType::New();
50 if (dim == 4) m_LastDimensionIsTime = true; // by default 4D is 3D+t
51 for(unsigned int i=0; i<dim; i++) {
53 m_OutputSpacing[i] = -1;
54 m_GaussianSigma[i] = -1;
56 m_VerboseOptions = false;
58 //--------------------------------------------------------------------
61 //--------------------------------------------------------------------
62 template <class TInputImage, class TOutputImage>
64 clitk::ResampleImageWithOptionsFilter<TInputImage, TOutputImage>::
65 SetInput(const InputImageType * image)
67 // Process object is not const-correct so the const casting is required.
68 this->SetNthInput(0, const_cast<InputImageType *>(image));
70 //--------------------------------------------------------------------
73 //--------------------------------------------------------------------
74 template <class TInputImage, class TOutputImage>
76 clitk::ResampleImageWithOptionsFilter<TInputImage, TOutputImage>::
77 GenerateInputRequestedRegion()
79 // call the superclass's implementation of this method
80 Superclass::GenerateInputRequestedRegion();
82 // get pointers to the input and output
83 InputImagePointer inputPtr =
84 const_cast< TInputImage *>( this->GetInput() );
86 // Request the entire input image
87 InputImageRegionType inputRegion;
88 inputRegion = inputPtr->GetLargestPossibleRegion();
89 inputPtr->SetRequestedRegion(inputRegion);
91 //--------------------------------------------------------------------
94 //--------------------------------------------------------------------
95 template <class TInputImage, class TOutputImage>
97 clitk::ResampleImageWithOptionsFilter<TInputImage, TOutputImage>::
98 GenerateOutputInformation()
100 static const unsigned int dim = InputImageType::ImageDimension;
103 if (!std::numeric_limits<InputImagePixelType>::is_signed) {
104 if ((m_InterpolationType == BSpline) ||
105 (m_InterpolationType == B_LUT)) {
106 std::cerr << "Warning : input pixel type is not signed, use bspline interpolation at your own risk ..." << std::endl;
111 InputImagePointer input = dynamic_cast<InputImageType*>(itk::ProcessObject::GetInput(0));
113 // Perform default implementation
114 Superclass::GenerateOutputInformation();
117 InputImageSpacingType inputSpacing = input->GetSpacing();
118 InputImageSizeType inputSize = input->GetLargestPossibleRegion().GetSize();
120 if (m_OutputIsoSpacing != -1) { // apply isoSpacing
121 for(unsigned int i=0; i<dim; i++) {
122 m_OutputSpacing[i] = m_OutputIsoSpacing;
123 m_OutputSize[i] = (int)lrint(inputSize[i]*inputSpacing[i]/m_OutputSpacing[i]);
126 if (m_OutputSpacing[0] != -1) { // apply spacing, compute size
127 for(unsigned int i=0; i<dim; i++) {
128 m_OutputSize[i] = (int)lrint(inputSize[i]*inputSpacing[i]/m_OutputSpacing[i]);
131 if (m_OutputSize[0] != 0) { // apply size, compute spacing
132 for(unsigned int i=0; i<dim; i++) {
133 m_OutputSpacing[i] = (double)inputSize[i]*inputSpacing[i]/(double)m_OutputSize[i];
135 } else { // copy input size/spacing ... (no resampling)
136 m_OutputSize = inputSize;
137 m_OutputSpacing = inputSpacing;
142 // Special case for temporal image 2D+t or 3D+t
143 if (m_LastDimensionIsTime) {
145 m_OutputSize[l] = inputSize[l];
146 m_OutputSpacing[l] = inputSpacing[l];
150 OutputImagePointer outputImage = this->GetOutput(0);
151 // OutputImageRegionType region;
152 m_OutputRegion.SetSize(m_OutputSize);
153 m_OutputRegion.SetIndex(input->GetLargestPossibleRegion().GetIndex());
154 outputImage->CopyInformation(input);
155 outputImage->SetLargestPossibleRegion(m_OutputRegion);
156 outputImage->SetSpacing(m_OutputSpacing);
158 // Init Gaussian sigma
159 if (m_GaussianSigma[0] != -1) { // Gaussian filter set by user
160 m_GaussianFilteringEnabled = true;
163 if (m_GaussianFilteringEnabled) { // Automated sigma when downsample
164 for(unsigned int i=0; i<dim; i++) {
165 if (m_OutputSpacing[i] > inputSpacing[i]) { // downsample
166 m_GaussianSigma[i] = 0.5*m_OutputSpacing[i];// / inputSpacing[i]);
168 else m_GaussianSigma[i] = 0; // will be ignore after
172 if (m_GaussianFilteringEnabled && m_LastDimensionIsTime) {
173 m_GaussianSigma[dim-1] = 0;
176 //--------------------------------------------------------------------
179 //--------------------------------------------------------------------
180 template <class TInputImage, class TOutputImage>
182 clitk::ResampleImageWithOptionsFilter<TInputImage, TOutputImage>::
187 InputImagePointer input = dynamic_cast<InputImageType*>(itk::ProcessObject::GetInput(0));
188 static const unsigned int dim = InputImageType::ImageDimension;
190 // Set regions and allocate
191 this->GetOutput()->SetRegions(m_OutputRegion);
192 this->GetOutput()->Allocate();
193 // this->GetOutput()->FillBuffer(m_DefaultPixelValue);
195 // Create main Resample Image Filter
196 typedef itk::ResampleImageFilter<InputImageType,OutputImageType> FilterType;
197 typename FilterType::Pointer filter = FilterType::New();
198 filter->GraftOutput(this->GetOutput());
199 // this->GetOutput()->Print(std::cout);
200 // this->GetOutput()->SetBufferedRegion(this->GetOutput()->GetLargestPossibleRegion());
201 // this->GetOutput()->Print(std::cout);
203 // Print options if needed
204 if (m_VerboseOptions) {
205 std::cout << "Output Spacing = " << m_OutputSpacing << std::endl
206 << "Output Size = " << m_OutputSize << std::endl
207 << "Gaussian = " << m_GaussianFilteringEnabled << std::endl;
208 if (m_GaussianFilteringEnabled)
209 std::cout << "Sigma = " << m_GaussianSigma << std::endl;
210 std::cout << "Interpol = ";
211 switch (m_InterpolationType) {
212 case NearestNeighbor: std::cout << "NearestNeighbor" << std::endl; break;
213 case Linear: std::cout << "Linear" << std::endl; break;
214 case BSpline: std::cout << "BSpline " << m_BSplineOrder << std::endl; break;
215 case B_LUT: std::cout << "B-LUT " << m_BSplineOrder << " " << m_BLUTSamplingFactor << std::endl; break;
217 std::cout << "Threads = " << this->GetNumberOfThreads() << std::endl;
218 std::cout << "LastDimIsTime = " << m_LastDimensionIsTime << std::endl;
221 // Instance of the transform object to be passed to the resample
222 // filter. By default, identity transform is applied
223 filter->SetTransform(m_Transform);
224 filter->SetSize(m_OutputSize);
225 filter->SetOutputSpacing(m_OutputSpacing);
226 filter->SetOutputOrigin(input->GetOrigin());
227 filter->SetDefaultPixelValue(m_DefaultPixelValue);
228 filter->SetNumberOfThreads(this->GetNumberOfThreads());
229 filter->SetOutputDirection(input->GetDirection()); // <-- NEEDED if we want to keep orientation (in case of PermutAxes for example)
231 // Select interpolator
232 switch (m_InterpolationType) {
233 case NearestNeighbor: {
234 typedef itk::NearestNeighborInterpolateImageFunction<InputImageType, double> InterpolatorType;
235 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
236 filter->SetInterpolator(interpolator);
240 typedef itk::LinearInterpolateImageFunction<InputImageType, double> InterpolatorType;
241 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
242 filter->SetInterpolator(interpolator);
246 typedef itk::BSplineInterpolateImageFunction<InputImageType, double> InterpolatorType;
247 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
248 interpolator->SetSplineOrder(m_BSplineOrder);
249 filter->SetInterpolator(interpolator);
253 typedef itk::BSplineInterpolateImageFunctionWithLUT<InputImageType, double> InterpolatorType;
254 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
255 interpolator->SetSplineOrder(m_BSplineOrder);
256 interpolator->SetLUTSamplingFactor(m_BLUTSamplingFactor);
257 filter->SetInterpolator(interpolator);
262 // Initial Gaussian blurring if needed
263 // TODO : replace by itk::DiscreteGaussianImageFilter for small sigma
264 typedef itk::RecursiveGaussianImageFilter<InputImageType, InputImageType> GaussianFilterType;
265 std::vector<typename GaussianFilterType::Pointer> gaussianFilters;
266 if (m_GaussianFilteringEnabled) {
267 for(unsigned int i=0; i<dim; i++) {
268 if (m_GaussianSigma[i] != 0) {
269 gaussianFilters.push_back(GaussianFilterType::New());
270 gaussianFilters[i]->SetDirection(i);
271 gaussianFilters[i]->SetOrder(GaussianFilterType::ZeroOrder);
272 gaussianFilters[i]->SetNormalizeAcrossScale(false);
273 gaussianFilters[i]->SetSigma(m_GaussianSigma[i]); // in millimeter !
274 if (gaussianFilters.size() == 1) { // first
275 gaussianFilters[0]->SetInput(input);
277 gaussianFilters[i]->SetInput(gaussianFilters[i-1]->GetOutput());
281 if (gaussianFilters.size() > 0) {
282 filter->SetInput(gaussianFilters[gaussianFilters.size()-1]->GetOutput());
283 } else filter->SetInput(input);
284 } else filter->SetInput(input);
290 // DD("before Graft");
291 this->GraftOutput(filter->GetOutput());
292 // DD("after Graft");
294 //--------------------------------------------------------------------