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_OutputOrigin.Fill(0);
58 m_OutputDirection.SetIdentity();
59 m_VerboseOptions = false;
60 SetDefaultPixelValue(0);
62 //--------------------------------------------------------------------
65 //--------------------------------------------------------------------
66 template <class InputImageType, class OutputImageType>
68 clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
69 SetInput(const InputImageType * image)
71 // Process object is not const-correct so the const casting is required.
72 this->SetNthInput(0, const_cast<InputImageType *>(image));
74 //--------------------------------------------------------------------
77 //--------------------------------------------------------------------
78 template <class InputImageType, class OutputImageType>
80 clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
81 GenerateInputRequestedRegion()
83 // call the superclass's implementation of this method
84 Superclass::GenerateInputRequestedRegion();
86 // get pointers to the input and output
87 InputImagePointer inputPtr =
88 const_cast< InputImageType *>( this->GetInput() );
90 // Request the entire input image
91 InputImageRegionType inputRegion;
92 inputRegion = inputPtr->GetLargestPossibleRegion();
93 inputPtr->SetRequestedRegion(inputRegion);
95 //--------------------------------------------------------------------
98 //--------------------------------------------------------------------
99 template <class InputImageType, class OutputImageType>
101 clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
102 GenerateOutputInformation()
104 static const unsigned int dim = InputImageType::ImageDimension;
107 if (!std::numeric_limits<InputImagePixelType>::is_signed) {
108 if ((m_InterpolationType == BSpline) ||
109 (m_InterpolationType == B_LUT)) {
110 std::cerr << "Warning : input pixel type is not signed, use bspline interpolation at your own risk ..." << std::endl;
115 InputImagePointer input = dynamic_cast<InputImageType*>(itk::ProcessObject::GetInput(0));
117 // Perform default implementation
118 Superclass::GenerateOutputInformation();
121 InputImageSpacingType inputSpacing = input->GetSpacing();
122 InputImageSizeType inputSize = input->GetLargestPossibleRegion().GetSize();
124 if (m_OutputIsoSpacing != -1) { // apply isoSpacing
125 for(unsigned int i=0; i<dim; i++) {
126 m_OutputSpacing[i] = m_OutputIsoSpacing;
127 // floor() is used to intentionally reduce the number of slices
128 // because, from a clinical point of view, it's better to
129 // remove data than to add data that privously didn't exist.
130 if(inputSpacing[i]*m_OutputSpacing[i]<0)
131 itkExceptionMacro( << "Input and output spacings don't have the same signs, can't cope with that" );
132 m_OutputSize[i] = (int)floor(inputSize[i]*inputSpacing[i]/m_OutputSpacing[i]);
135 else if(m_OutputSpacing[0]==-1 || m_OutputSize[0]==0){
136 if (m_OutputSpacing[0] != -1) { // apply spacing, compute size
137 for(unsigned int i=0; i<dim; i++) {
138 if(inputSpacing[i]*m_OutputSpacing[i]<0) {
139 itkExceptionMacro( << "Input and output spacings don't have the same signs, can't cope with that" );
141 // see comment above for the use of floor()
142 m_OutputSize[i] = (int)floor(inputSize[i]*inputSpacing[i]/m_OutputSpacing[i]);
146 if (m_OutputSize[0] != 0) { // apply size, compute spacing
147 for(unsigned int i=0; i<dim; i++) {
148 m_OutputSpacing[i] = (double)inputSize[i]*inputSpacing[i]/(double)m_OutputSize[i];
151 else { // copy input size/spacing ... (no resampling)
152 m_OutputSize = inputSize;
153 m_OutputSpacing = inputSpacing;
158 // Special case for temporal image 2D+t or 3D+t
159 if (m_LastDimensionIsTime) {
161 m_OutputSize[l] = inputSize[l];
162 m_OutputSpacing[l] = inputSpacing[l];
166 OutputImagePointer outputImage = this->GetOutput(0);
167 // OutputImageRegionType region;
168 m_OutputRegion.SetSize(m_OutputSize);
169 m_OutputRegion.SetIndex(input->GetLargestPossibleRegion().GetIndex());
170 outputImage->CopyInformation(input);
171 outputImage->SetLargestPossibleRegion(m_OutputRegion);
172 outputImage->SetSpacing(m_OutputSpacing);
174 // Init Gaussian sigma
175 if (m_GaussianSigma[0] != -1) { // Gaussian filter set by user
176 m_GaussianFilteringEnabled = true;
179 if (m_GaussianFilteringEnabled) { // Automated sigma when downsample
180 for(unsigned int i=0; i<dim; i++) {
181 if (m_OutputSpacing[i] > inputSpacing[i]) { // downsample
182 m_GaussianSigma[i] = 0.5*m_OutputSpacing[i];// / inputSpacing[i]);
184 else m_GaussianSigma[i] = 0; // will be ignore after
188 if (m_GaussianFilteringEnabled && m_LastDimensionIsTime) {
189 m_GaussianSigma[dim-1] = 0;
192 //--------------------------------------------------------------------
195 //--------------------------------------------------------------------
196 template <class InputImageType, class OutputImageType>
198 clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
203 InputImagePointer input = dynamic_cast<InputImageType*>(itk::ProcessObject::GetInput(0));
204 static const unsigned int dim = InputImageType::ImageDimension;
206 // Create main Resample Image Filter
207 typedef itk::ResampleImageFilter<InputImageType,OutputImageType> FilterType;
208 typename FilterType::Pointer filter = FilterType::New();
209 filter->GraftOutput(this->GetOutput());
210 this->GetOutput()->SetBufferedRegion(this->GetOutput()->GetLargestPossibleRegion());
212 // Print options if needed
213 if (m_VerboseOptions) {
214 std::cout << "Output Spacing = " << m_OutputSpacing << std::endl
215 << "Output Size = " << m_OutputSize << std::endl
216 << "Gaussian = " << m_GaussianFilteringEnabled << std::endl;
217 if (m_GaussianFilteringEnabled)
218 std::cout << "Sigma = " << m_GaussianSigma << std::endl;
219 std::cout << "Interpol = ";
220 switch (m_InterpolationType) {
221 case NearestNeighbor: std::cout << "NearestNeighbor" << std::endl; break;
222 case Linear: std::cout << "Linear" << std::endl; break;
223 case BSpline: std::cout << "BSpline " << m_BSplineOrder << std::endl; break;
224 case B_LUT: std::cout << "B-LUT " << m_BSplineOrder << " " << m_BLUTSamplingFactor << std::endl; break;
225 case WSINC: std::cout << "Windowed Sinc" << std::endl; break;
227 std::cout << "Threads = " << this->GetNumberOfThreads() << std::endl;
228 std::cout << "LastDimIsTime = " << m_LastDimensionIsTime << std::endl;
231 // Compute origin based on image corner
232 for(unsigned int i=0; i<OutputImageType::ImageDimension; i++) {
233 m_OutputOrigin[i] -= 0.5 * input->GetSpacing()[i];
234 m_OutputOrigin[i] += 0.5 * m_OutputSpacing[i];
237 // Instance of the transform object to be passed to the resample
238 // filter. By default, identity transform is applied
239 filter->SetTransform(m_Transform);
240 filter->SetSize(m_OutputSize);
241 filter->SetOutputSpacing(m_OutputSpacing);
242 filter->SetOutputOrigin(m_OutputOrigin);
243 filter->SetDefaultPixelValue(m_DefaultPixelValue);
244 filter->SetNumberOfThreads(this->GetNumberOfThreads());
245 filter->SetOutputDirection(m_OutputDirection); // <-- NEEDED if we want to keep orientation (in case of PermutAxes for example)
247 // Select interpolator
248 switch (m_InterpolationType) {
249 case NearestNeighbor: {
250 typedef itk::NearestNeighborInterpolateImageFunction<InputImageType, double> InterpolatorType;
251 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
252 filter->SetInterpolator(interpolator);
256 typedef itk::LinearInterpolateImageFunction<InputImageType, double> InterpolatorType;
257 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
258 filter->SetInterpolator(interpolator);
262 typedef itk::BSplineInterpolateImageFunction<InputImageType, double> InterpolatorType;
263 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
264 interpolator->SetSplineOrder(m_BSplineOrder);
265 filter->SetInterpolator(interpolator);
269 typedef itk::BSplineInterpolateImageFunctionWithLUT<InputImageType, double> InterpolatorType;
270 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
271 interpolator->SetSplineOrder(m_BSplineOrder);
272 interpolator->SetLUTSamplingFactor(m_BLUTSamplingFactor);
273 filter->SetInterpolator(interpolator);
277 typedef itk::WindowedSincInterpolateImageFunction<InputImageType, 4> InterpolatorType;
278 typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
279 filter->SetInterpolator(interpolator);
284 // Initial Gaussian blurring if needed
285 // TODO : replace by itk::DiscreteGaussianImageFilter for small sigma
286 typedef itk::RecursiveGaussianImageFilter<InputImageType, InputImageType> GaussianFilterType;
287 std::vector<typename GaussianFilterType::Pointer> gaussianFilters;
288 if (m_GaussianFilteringEnabled) {
289 for(unsigned int i=0; i<dim; i++) {
290 if (m_GaussianSigma[i] != 0) {
291 gaussianFilters.push_back(GaussianFilterType::New());
292 gaussianFilters[i]->SetDirection(i);
293 gaussianFilters[i]->SetOrder(GaussianFilterType::ZeroOrder);
294 gaussianFilters[i]->SetNormalizeAcrossScale(false);
295 gaussianFilters[i]->SetSigma(m_GaussianSigma[i]); // in millimeter !
296 if (gaussianFilters.size() == 1) { // first
297 gaussianFilters[0]->SetInput(input);
299 gaussianFilters[i]->SetInput(gaussianFilters[i-1]->GetOutput());
303 if (gaussianFilters.size() > 0) {
304 filter->SetInput(gaussianFilters[gaussianFilters.size()-1]->GetOutput());
305 } else filter->SetInput(input);
306 } else filter->SetInput(input);
312 this->GraftOutput(filter->GetOutput());
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 //--------------------------------------------------------------------