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://www.centreleonberard.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 ===========================================================================**/
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 "itkWindowedSincInterpolateImageFunction.h"
32 #include "itkLinearInterpolateImageFunction.h"
33 #include "itkBSplineInterpolateImageFunction.h"
34 #include "itkBSplineInterpolateImageFunctionWithLUT.h"
35 #include "itkCommand.h"
37 //--------------------------------------------------------------------
38 template <class InputImageType, class OutputImageType>
39 clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
40 ResampleImageWithOptionsFilter():itk::ImageToImageFilter<InputImageType, OutputImageType>()
42 static const unsigned int dim = InputImageType::ImageDimension;
43 this->SetNumberOfRequiredInputs(1);
44 m_OutputIsoSpacing = -1;
45 m_InterpolationType = NearestNeighbor;
46 m_GaussianFilteringEnabled = true;
48 m_BLUTSamplingFactor = 20;
49 m_LastDimensionIsTime = false;
50 m_Transform = TransformType::New();
51 if (dim == 4) m_LastDimensionIsTime = true; // by default 4D is 3D+t
52 for(unsigned int i=0; i<dim; i++) {
54 m_OutputSpacing[i] = -1;
55 m_GaussianSigma[i] = -1;
57 m_VerboseOptions = false;
58 SetDefaultPixelValue(0);
60 //--------------------------------------------------------------------
63 //--------------------------------------------------------------------
64 template <class InputImageType, class OutputImageType>
66 clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
67 SetInput(const InputImageType * image)
69 // Process object is not const-correct so the const casting is required.
70 this->SetNthInput(0, const_cast<InputImageType *>(image));
72 //--------------------------------------------------------------------
75 //--------------------------------------------------------------------
76 template <class InputImageType, class OutputImageType>
78 clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
79 GenerateInputRequestedRegion()
81 // call the superclass's implementation of this method
82 Superclass::GenerateInputRequestedRegion();
84 // get pointers to the input and output
85 InputImagePointer inputPtr =
86 const_cast< InputImageType *>( this->GetInput() );
88 // Request the entire input image
89 InputImageRegionType inputRegion;
90 inputRegion = inputPtr->GetLargestPossibleRegion();
91 inputPtr->SetRequestedRegion(inputRegion);
93 //--------------------------------------------------------------------
96 //--------------------------------------------------------------------
97 template <class InputImageType, class OutputImageType>
99 clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
100 GenerateOutputInformation()
102 static const unsigned int dim = InputImageType::ImageDimension;
105 if (!std::numeric_limits<InputImagePixelType>::is_signed) {
106 if ((m_InterpolationType == BSpline) ||
107 (m_InterpolationType == B_LUT)) {
108 std::cerr << "Warning : input pixel type is not signed, use bspline interpolation at your own risk ..." << std::endl;
113 InputImagePointer input = dynamic_cast<InputImageType*>(itk::ProcessObject::GetInput(0));
115 // Perform default implementation
116 Superclass::GenerateOutputInformation();
119 InputImageSpacingType inputSpacing = input->GetSpacing();
120 InputImageSizeType inputSize = input->GetLargestPossibleRegion().GetSize();
122 if (m_OutputIsoSpacing != -1) { // apply isoSpacing
123 for(unsigned int i=0; i<dim; i++) {
124 m_OutputSpacing[i] = m_OutputIsoSpacing;
125 // floor() is used to intentionally reduce the number of slices
126 // because, from a clinical point of view, it's better to
127 // remove data than to add data that privously didn't exist.
128 if(inputSpacing[i]*m_OutputSpacing[i]<0)
129 itkExceptionMacro( << "Input and output spacings don't have the same signs, can't cope with that" );
130 m_OutputSize[i] = (int)floor(inputSize[i]*inputSpacing[i]/m_OutputSpacing[i]);
133 if (m_OutputSpacing[0] != -1) { // apply spacing, compute size
134 for(unsigned int i=0; i<dim; i++) {
135 if(inputSpacing[i]*m_OutputSpacing[i]<0)
136 itkExceptionMacro( << "Input and output spacings don't have the same signs, can't cope with that" );
137 // see comment above for the use of floor()
138 m_OutputSize[i] = (int)floor(inputSize[i]*inputSpacing[i]/m_OutputSpacing[i]);
141 if (m_OutputSize[0] != 0) { // apply size, compute spacing
142 for(unsigned int i=0; i<dim; i++) {
143 m_OutputSpacing[i] = (double)inputSize[i]*inputSpacing[i]/(double)m_OutputSize[i];
145 } else { // copy input size/spacing ... (no resampling)
146 m_OutputSize = inputSize;
147 m_OutputSpacing = inputSpacing;
152 // Special case for temporal image 2D+t or 3D+t
153 if (m_LastDimensionIsTime) {
155 m_OutputSize[l] = inputSize[l];
156 m_OutputSpacing[l] = inputSpacing[l];
160 OutputImagePointer outputImage = this->GetOutput(0);
161 // OutputImageRegionType region;
162 m_OutputRegion.SetSize(m_OutputSize);
163 m_OutputRegion.SetIndex(input->GetLargestPossibleRegion().GetIndex());
164 outputImage->CopyInformation(input);
165 outputImage->SetLargestPossibleRegion(m_OutputRegion);
166 outputImage->SetSpacing(m_OutputSpacing);
168 // Init Gaussian sigma
169 if (m_GaussianSigma[0] != -1) { // Gaussian filter set by user
170 m_GaussianFilteringEnabled = true;
173 if (m_GaussianFilteringEnabled) { // Automated sigma when downsample
174 for(unsigned int i=0; i<dim; i++) {
175 if (m_OutputSpacing[i] > inputSpacing[i]) { // downsample
176 m_GaussianSigma[i] = 0.5*m_OutputSpacing[i];// / inputSpacing[i]);
178 else m_GaussianSigma[i] = 0; // will be ignore after
182 if (m_GaussianFilteringEnabled && m_LastDimensionIsTime) {
183 m_GaussianSigma[dim-1] = 0;
186 //--------------------------------------------------------------------
189 //--------------------------------------------------------------------
190 template <class InputImageType, class OutputImageType>
192 clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
197 InputImagePointer input = dynamic_cast<InputImageType*>(itk::ProcessObject::GetInput(0));
198 static const unsigned int dim = InputImageType::ImageDimension;
200 // Create main Resample Image Filter
201 typedef itk::ResampleImageFilter<InputImageType,OutputImageType> FilterType;
202 typename FilterType::Pointer filter = FilterType::New();
203 filter->GraftOutput(this->GetOutput());
204 this->GetOutput()->SetBufferedRegion(this->GetOutput()->GetLargestPossibleRegion());
206 // Print options if needed
207 if (m_VerboseOptions) {
208 std::cout << "Output Spacing = " << m_OutputSpacing << std::endl
209 << "Output Size = " << m_OutputSize << std::endl
210 << "Gaussian = " << m_GaussianFilteringEnabled << std::endl;
211 if (m_GaussianFilteringEnabled)
212 std::cout << "Sigma = " << m_GaussianSigma << std::endl;
213 std::cout << "Interpol = ";
214 switch (m_InterpolationType) {
215 case NearestNeighbor: std::cout << "NearestNeighbor" << std::endl; break;
216 case Linear: std::cout << "Linear" << std::endl; break;
217 case BSpline: std::cout << "BSpline " << m_BSplineOrder << std::endl; break;
218 case B_LUT: std::cout << "B-LUT " << m_BSplineOrder << " " << m_BLUTSamplingFactor << std::endl; break;
219 case WSINC: std::cout << "Windowed Sinc" << std::endl; break;
221 std::cout << "Threads = " << this->GetNumberOfThreads() << std::endl;
222 std::cout << "LastDimIsTime = " << m_LastDimensionIsTime << std::endl;
225 // Compute origin based on image corner
226 typename FilterType::OriginPointType origin = input->GetOrigin();
227 for(unsigned int i=0; i<OutputImageType::ImageDimension; i++) {
228 origin[i] -= 0.5 * input->GetSpacing()[i];
229 origin[i] += 0.5 * m_OutputSpacing[i];
232 // Instance of the transform object to be passed to the resample
233 // filter. By default, identity transform is applied
234 filter->SetTransform(m_Transform);
235 filter->SetSize(m_OutputSize);
236 filter->SetOutputSpacing(m_OutputSpacing);
237 filter->SetOutputOrigin(origin);
238 filter->SetDefaultPixelValue(m_DefaultPixelValue);
239 filter->SetNumberOfThreads(this->GetNumberOfThreads());
240 filter->SetOutputDirection(input->GetDirection()); // <-- NEEDED if we want to keep orientation (in case of PermutAxes for example)
242 // Select interpolator
243 switch (m_InterpolationType) {
244 case NearestNeighbor: {
245 typedef itk::NearestNeighborInterpolateImageFunction<InputImageType, double> InterpolatorType;
246 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
247 filter->SetInterpolator(interpolator);
251 typedef itk::LinearInterpolateImageFunction<InputImageType, double> InterpolatorType;
252 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
253 filter->SetInterpolator(interpolator);
257 typedef itk::BSplineInterpolateImageFunction<InputImageType, double> InterpolatorType;
258 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
259 interpolator->SetSplineOrder(m_BSplineOrder);
260 filter->SetInterpolator(interpolator);
264 typedef itk::BSplineInterpolateImageFunctionWithLUT<InputImageType, double> InterpolatorType;
265 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
266 interpolator->SetSplineOrder(m_BSplineOrder);
267 interpolator->SetLUTSamplingFactor(m_BLUTSamplingFactor);
268 filter->SetInterpolator(interpolator);
272 typedef itk::WindowedSincInterpolateImageFunction<InputImageType, 4> InterpolatorType;
273 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
274 filter->SetInterpolator(interpolator);
279 // Initial Gaussian blurring if needed
280 // TODO : replace by itk::DiscreteGaussianImageFilter for small sigma
281 typedef itk::RecursiveGaussianImageFilter<InputImageType, InputImageType> GaussianFilterType;
282 std::vector<typename GaussianFilterType::Pointer> gaussianFilters;
283 if (m_GaussianFilteringEnabled) {
284 for(unsigned int i=0; i<dim; i++) {
285 if (m_GaussianSigma[i] != 0) {
286 gaussianFilters.push_back(GaussianFilterType::New());
287 gaussianFilters[i]->SetDirection(i);
288 gaussianFilters[i]->SetOrder(GaussianFilterType::ZeroOrder);
289 gaussianFilters[i]->SetNormalizeAcrossScale(false);
290 gaussianFilters[i]->SetSigma(m_GaussianSigma[i]); // in millimeter !
291 if (gaussianFilters.size() == 1) { // first
292 gaussianFilters[0]->SetInput(input);
294 gaussianFilters[i]->SetInput(gaussianFilters[i-1]->GetOutput());
298 if (gaussianFilters.size() > 0) {
299 filter->SetInput(gaussianFilters[gaussianFilters.size()-1]->GetOutput());
300 } else filter->SetInput(input);
301 } else filter->SetInput(input);
307 // DD("before Graft");
309 //this->GraftOutput(filter->GetOutput());
310 this->SetNthOutput(0, filter->GetOutput());
312 // DD("after Graft");
314 //--------------------------------------------------------------------
317 //--------------------------------------------------------------------
318 template<class InputImageType>
319 typename InputImageType::Pointer
320 clitk::ResampleImageSpacing(typename InputImageType::Pointer input,
321 typename InputImageType::SpacingType spacing,
322 int interpolationType)
324 typedef clitk::ResampleImageWithOptionsFilter<InputImageType> ResampleFilterType;
325 typename ResampleFilterType::Pointer resampler = ResampleFilterType::New();
326 resampler->SetInput(input);
327 resampler->SetOutputSpacing(spacing);
328 typename ResampleFilterType::InterpolationTypeEnumeration inter=ResampleFilterType::NearestNeighbor;
329 switch(interpolationType) {
330 case 0: inter = ResampleFilterType::NearestNeighbor; break;
331 case 1: inter = ResampleFilterType::Linear; break;
332 case 2: inter = ResampleFilterType::BSpline; break;
333 case 3: inter = ResampleFilterType::B_LUT; break;
334 case 4: inter = ResampleFilterType::WSINC; break;
336 resampler->SetInterpolationType(inter);
337 resampler->SetGaussianFilteringEnabled(true);
339 return resampler->GetOutput();
341 //--------------------------------------------------------------------