File: itkDemonsImageToImageMetricv4RegistrationTest.cxx

package info (click to toggle)
insighttoolkit4 4.13.3withdata-dfsg2-4
  • links: PTS, VCS
  • area: main
  • in suites: bookworm
  • size: 491,256 kB
  • sloc: cpp: 557,600; ansic: 180,546; fortran: 34,788; python: 16,572; sh: 2,187; lisp: 2,070; tcl: 993; java: 362; perl: 200; makefile: 133; csh: 81; pascal: 69; xml: 19; ruby: 10
file content (312 lines) | stat: -rw-r--r-- 12,433 bytes parent folder | download | duplicates (5)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
/*=========================================================================
*
*  Copyright Insight Software Consortium
*
*  Licensed under the Apache License, Version 2.0 (the "License");
*  you may not use this file except in compliance with the License.
*  You may obtain a copy of the License at
*
*         http://www.apache.org/licenses/LICENSE-2.0.txt
*
*  Unless required by applicable law or agreed to in writing, software
*  distributed under the License is distributed on an "AS IS" BASIS,
*  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
*  See the License for the specific language governing permissions and
*  limitations under the License.
*
*=========================================================================*/

/**
 * Test program for itkDemonsImageToImageMetricv4 and
 * GradientDescentOptimizerv4 classes.
 *
 * Perform a registration using user-supplied images.
 * No numerical verification is performed. Test passes as long
 * as no exception occurs.
 */
#include "itkDemonsImageToImageMetricv4.h"
#include "itkGradientDescentOptimizerv4.h"
#include "itkRegistrationParameterScalesFromPhysicalShift.h"

#include "itkGaussianSmoothingOnUpdateDisplacementFieldTransform.h"

#include "itkCastImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"
#include "itkHistogramMatchingImageFilter.h"
#include "itkCommand.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"

#include <iomanip>

#include "itkCommand.h"

#include <iostream>
#include <fstream>

template<typename TFilter>
class itkDemonsImageToImageMetricv4RegistrationTestCommandIterationUpdate : public itk::Command
{
public:
  typedef itkDemonsImageToImageMetricv4RegistrationTestCommandIterationUpdate   Self;

  typedef itk::Command             Superclass;
  typedef itk::SmartPointer<Self>  Pointer;
  itkNewMacro( Self );

protected:
  itkDemonsImageToImageMetricv4RegistrationTestCommandIterationUpdate() {};

public:

  virtual void Execute(itk::Object *caller, const itk::EventObject & event) ITK_OVERRIDE
    {
    Execute( (const itk::Object *) caller, event);
    }

  virtual void Execute(const itk::Object * object, const itk::EventObject & event) ITK_OVERRIDE
    {
    if( typeid( event ) != typeid( itk::IterationEvent ) )
      {
      return;
      }
    const TFilter *optimizer = static_cast< const TFilter * >( object );

    std::cout << "It: " << optimizer->GetCurrentIteration() << " metric value: " << optimizer->GetValue();
    std::cout << std::endl;
    }
};

int itkDemonsImageToImageMetricv4RegistrationTest(int argc, char *argv[])
{

  if( argc < 4 )
    {
    std::cerr << "Missing Parameters " << std::endl;
    std::cerr << "Usage: " << argv[0];
    std::cerr << " fixedImageFile movingImageFile ";
    std::cerr << " outputImageFile ";
    std::cerr << " [numberOfIterations = 10] ";
    std::cerr << " [doSampling = false] ";
    std::cerr << " [useImageGradientFilter = false]";
    std::cerr << std::endl;
    return EXIT_FAILURE;
    }

  std::cout << argc << std::endl;
  unsigned int numberOfIterations = 10;
  bool doSampling = false;
  bool useImageGradientFilter = false;
  if( argc >= 5 )
    {
    numberOfIterations = atoi( argv[4] );
    }
  if( argc >= 6 )
    {
    doSampling = atoi( argv[5] );
    }
  if( argc >= 7 )
    {
    useImageGradientFilter = atoi( argv[6] );
    }

  std::cout << " iterations "<< numberOfIterations << std::endl;
  std::cout << " useImageGradientFilter " << useImageGradientFilter << std::endl;

  const unsigned int Dimension = 2;
  typedef double PixelType; //I assume png is unsigned short

  typedef itk::Image< PixelType, Dimension >  FixedImageType;
  typedef itk::Image< PixelType, Dimension >  MovingImageType;

  typedef itk::ImageFileReader< FixedImageType  > FixedImageReaderType;
  typedef itk::ImageFileReader< MovingImageType > MovingImageReaderType;

  FixedImageReaderType::Pointer fixedImageReader   = FixedImageReaderType::New();
  MovingImageReaderType::Pointer movingImageReader = MovingImageReaderType::New();

  fixedImageReader->SetFileName( argv[1] );
  movingImageReader->SetFileName( argv[2] );

  //get the images
  fixedImageReader->Update();
  FixedImageType::Pointer  fixedImage = fixedImageReader->GetOutput();
  movingImageReader->Update();
  MovingImageType::Pointer movingImage = movingImageReader->GetOutput();

  // scale the images to [0,1]
  typedef itk::RescaleIntensityImageFilter<FixedImageType, FixedImageType> FixedRescaleFilterType;
  FixedRescaleFilterType::Pointer fixedRescaleFilter = FixedRescaleFilterType::New();
  fixedRescaleFilter->SetInput( fixedImage );
  fixedRescaleFilter->SetOutputMinimum( itk::NumericTraits<PixelType>::ZeroValue() );
  fixedRescaleFilter->SetOutputMaximum( itk::NumericTraits<PixelType>::OneValue() );
  fixedRescaleFilter->Update();
  fixedImage = fixedRescaleFilter->GetOutput();

  typedef itk::RescaleIntensityImageFilter<MovingImageType, MovingImageType> MovingRescaleFilterType;
  MovingRescaleFilterType::Pointer movingRescaleFilter = MovingRescaleFilterType::New();
  movingRescaleFilter->SetInput( movingImage );
  movingRescaleFilter->SetOutputMinimum( itk::NumericTraits<PixelType>::ZeroValue() );
  movingRescaleFilter->SetOutputMaximum( itk::NumericTraits<PixelType>::OneValue() );
  movingRescaleFilter->Update();
  movingImage = movingRescaleFilter->GetOutput();

  // histogram matching of values
  typedef itk::HistogramMatchingImageFilter<FixedImageType, MovingImageType> MatchingFilterType;
  MatchingFilterType::Pointer matchingFilter = MatchingFilterType::New();
  matchingFilter->SetInput( movingImage );
  matchingFilter->SetReferenceImage( fixedImage );
  matchingFilter->ThresholdAtMeanIntensityOn();
  matchingFilter->SetNumberOfHistogramLevels( 256 ); //from ANTS
  matchingFilter->SetNumberOfMatchPoints( 12 ); //from ANTS
  matchingFilter->Update();
  movingImage = matchingFilter->GetOutput();

  /** Displacement field transform */
  typedef itk::GaussianSmoothingOnUpdateDisplacementFieldTransform< double, Dimension> DisplacementTransformType;
  DisplacementTransformType::Pointer displacementTransform = DisplacementTransformType::New();

  typedef DisplacementTransformType::DisplacementFieldType DisplacementFieldType;
  DisplacementFieldType::Pointer field = DisplacementFieldType::New();

  // set the field to be the same as the fixed image region, which will
  // act by default as the virtual domain in this example.
  field->SetRegions( fixedImage->GetLargestPossibleRegion() );
  //make sure the field has the same spatial information as the image
  field->CopyInformation( fixedImage );
  std::cout << "fixedImage->GetLargestPossibleRegion(): "
            << fixedImage->GetLargestPossibleRegion() << std::endl;
  field->Allocate();
  // Fill it with 0's
  DisplacementTransformType::OutputVectorType zeroVector;
  zeroVector.Fill( 0 );
  field->FillBuffer( zeroVector );
  // Assign to transform
  displacementTransform->SetDisplacementField( field );
  displacementTransform->SetGaussianSmoothingVarianceForTheUpdateField( 5 );
  displacementTransform->SetGaussianSmoothingVarianceForTheTotalField( 6 );

  // The metric
  typedef itk::DemonsImageToImageMetricv4 < FixedImageType, MovingImageType >  MetricType;
  typedef MetricType::FixedSampledPointSetType                                 PointSetType;
  MetricType::Pointer metric = MetricType::New();

  // Assign images and transforms.
  metric->SetFixedImage( fixedImage );
  metric->SetMovingImage( movingImage );
  metric->SetMovingTransform( displacementTransform );
  metric->SetUseMovingImageGradientFilter( useImageGradientFilter );
  metric->SetUseFixedImageGradientFilter( useImageGradientFilter );

  // Sampling
  if( ! doSampling )
    {
    std::cout << "Dense sampling." << std::endl;
    metric->SetUseFixedSampledPointSet( false );
    }
  else
    {
    typedef PointSetType::PointType     PointType;
    PointSetType::Pointer               pset(PointSetType::New());
    unsigned long ind=0,ct=0;
    itk::ImageRegionIteratorWithIndex<FixedImageType> It(fixedImage, fixedImage->GetLargestPossibleRegion() );
    for( It.GoToBegin(); !It.IsAtEnd(); ++It )
      {
      // take every N^th point
      if ( ct % 10 == 0  )
        {
          PointType pt;
          fixedImage->TransformIndexToPhysicalPoint( It.GetIndex(), pt);
          pset->SetPoint(ind, pt);
          ind++;
        }
        ct++;
      }
    std::cout << "Setting point set with " << ind << " points of " << fixedImage->GetLargestPossibleRegion().GetNumberOfPixels() << " total " << std::endl;
    metric->SetFixedSampledPointSet( pset );
    metric->SetUseFixedSampledPointSet( true );
    std::cout << "Testing metric with point set..." << std::endl;
    }

  // Initialize
  metric->Initialize();

  // scales & step estimator
  typedef itk::RegistrationParameterScalesFromPhysicalShift< MetricType > RegistrationParameterScalesFromShiftType;
  RegistrationParameterScalesFromShiftType::Pointer shiftScaleEstimator = RegistrationParameterScalesFromShiftType::New();
  shiftScaleEstimator->SetMetric(metric);

  // Optimizer
  typedef itk::GradientDescentOptimizerv4  OptimizerType;
  OptimizerType::Pointer  optimizer = OptimizerType::New();
  optimizer->SetMetric( metric );
  optimizer->SetNumberOfIterations( numberOfIterations );
  optimizer->SetScalesEstimator( shiftScaleEstimator );

  try
    {
    optimizer->StartOptimization();
    }
  catch( itk::ExceptionObject & e )
    {
    std::cout << "Exception thrown ! " << std::endl;
    std::cout << "An error ocurred during deformation Optimization:" << std::endl;
    std::cout << e.GetLocation() << std::endl;
    std::cout << e.GetDescription() << std::endl;
    std::cout << e.what()    << std::endl;
    std::cout << "Test FAILED." << std::endl;
    return EXIT_FAILURE;
    }
  std::cout << "...finished. " << std::endl;

  if( doSampling )
    {
    std::cout << "GetNumberOfSkippedFixedSampledPoints: " << metric->GetNumberOfSkippedFixedSampledPoints() << std::endl;
    }

  //std::cout << "\n\n*gradient: " << optimizer->GetGradient() << std::endl;
  std::cout << "Scales: " << optimizer->GetScales() << std::endl;
  std::cout << "Final learning rate: " << optimizer->GetLearningRate() << std::endl;
  std::cout << "MaxStepSizeinPhysUnits: " << optimizer->GetMaximumStepSizeInPhysicalUnits() << std::endl;

  //warp the image with the displacement field
  typedef itk::ResampleImageFilter< MovingImageType, FixedImageType >    ResampleFilterType;
  ResampleFilterType::Pointer resample = ResampleFilterType::New();

  resample->SetTransform( displacementTransform );
  resample->SetInput( movingImageReader->GetOutput() );
  resample->SetSize(    fixedImage->GetLargestPossibleRegion().GetSize() );
  resample->SetOutputOrigin(  fixedImage->GetOrigin() );
  resample->SetOutputSpacing( fixedImage->GetSpacing() );
  resample->SetOutputDirection( fixedImage->GetDirection() );
  resample->SetDefaultPixelValue( 0 );
  resample->Update();

  //write out the displacement field
  typedef itk::ImageFileWriter< DisplacementFieldType >  DisplacementWriterType;
  DisplacementWriterType::Pointer      displacementwriter =  DisplacementWriterType::New();
  std::string outfilename( argv[3] );
  std::string  ext = itksys::SystemTools::GetFilenameExtension( outfilename );
  std::string name = itksys::SystemTools::GetFilenameWithoutExtension( outfilename );
  std::string path = itksys::SystemTools::GetFilenamePath( outfilename );
  std::string defout = path + std::string( "/" ) + name + std::string("_def") + ext;
  displacementwriter->SetFileName( defout.c_str() );
  displacementwriter->SetInput( displacementTransform->GetDisplacementField() );
  displacementwriter->Update();

  //write the warped image into a file
  typedef double                                                    OutputPixelType;
  typedef itk::Image< OutputPixelType, Dimension >                  OutputImageType;
  typedef itk::CastImageFilter< MovingImageType, OutputImageType >  CastFilterType;
  typedef itk::ImageFileWriter< OutputImageType >                   WriterType;

  WriterType::Pointer      writer =  WriterType::New();
  CastFilterType::Pointer  caster =  CastFilterType::New();
  writer->SetFileName( argv[3] );
  caster->SetInput( resample->GetOutput() );
  writer->SetInput( caster->GetOutput() );
  writer->Update();

  std::cout << "Test finished." << std::endl;
  return EXIT_SUCCESS;
}