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
|
/*=========================================================================
*
* 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 itkMultiStartImageToImageMetricv4RegistrationTest and
* GradientDescentOptimizerv4 classes.
*
* Perform a registration using user-supplied images.
* No numerical verification is performed. Test passes as long
* as no exception occurs.
*/
#include "itkMattesMutualInformationImageToImageMetricv4.h"
#include "itkJointHistogramMutualInformationImageToImageMetricv4.h"
#include "itkMeanSquaresImageToImageMetricv4.h"
#include "itkCorrelationImageToImageMetricv4.h"
#include "itkGradientDescentOptimizerv4.h"
#include "itkRegistrationParameterScalesFromPhysicalShift.h"
#include "itkMultiStartOptimizerv4.h"
#include "itkGaussianSmoothingOnUpdateDisplacementFieldTransform.h"
#include "itkCastImageFilter.h"
#include "itkCommand.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include <iomanip>
int itkMultiStartImageToImageMetricv4RegistrationTest(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 bool_rotate_input_image_by_180 ] ";
std::cerr << std::endl;
return EXIT_FAILURE;
}
std::cout << argc << std::endl;
unsigned int numberOfIterations = 10;
if( argc >= 5 )
{
numberOfIterations = atoi( argv[4] );
}
std::cout << " iterations "<< numberOfIterations << std::endl;
bool rotateinput=false;
if( argc > 5 )
if ( atoi(argv[5]) == 1 ) rotateinput=true;
const unsigned int Dimension = 2;
typedef unsigned short PixelType; //I assume png is unsigned short
typedef double InternalPixelType;
typedef itk::Image< PixelType, Dimension > InputImageType;
typedef itk::Image< InternalPixelType, Dimension > InternalImageType;
typedef itk::ImageFileReader< InputImageType > FixedImageReaderType;
typedef itk::ImageFileReader< InputImageType > MovingImageReaderType;
FixedImageReaderType::Pointer fixedImageReader = FixedImageReaderType::New();
fixedImageReader->SetFileName( argv[1] );
fixedImageReader->Update();
MovingImageReaderType::Pointer movingImageReader = MovingImageReaderType::New();
movingImageReader->SetFileName( argv[2] );
movingImageReader->Update();
//get the images
typedef itk::CastImageFilter<
InputImageType,
InternalImageType > CastFilterType;
CastFilterType::Pointer fixedcaster = CastFilterType::New();
fixedcaster->SetInput( fixedImageReader->GetOutput() ); // resample->GetOutput()
fixedcaster->Update();
InternalImageType::Pointer fixedImage = fixedcaster->GetOutput();
//get the images
CastFilterType::Pointer movingcaster = CastFilterType::New();
movingcaster->SetInput( movingImageReader->GetOutput() );
movingcaster->Update();
InternalImageType::Pointer movingImage = movingcaster->GetOutput();
/** Now set up a rotation about the center of the image */
//create an affine transform
typedef itk::AffineTransform<double, Dimension>
AffineTransformType;
InternalImageType::IndexType centerindex;
InternalImageType::PointType mpoint;
InternalImageType::PointType fpoint;
centerindex[0]=movingImage->GetLargestPossibleRegion().GetSize()[0]/2;
centerindex[1]=movingImage->GetLargestPossibleRegion().GetSize()[1]/2;
movingImage->TransformIndexToPhysicalPoint(centerindex,mpoint);
centerindex[0]=fixedImage->GetLargestPossibleRegion().GetSize()[0]/2;
centerindex[1]=fixedImage->GetLargestPossibleRegion().GetSize()[1]/2;
fixedImage->TransformIndexToPhysicalPoint(centerindex,fpoint);
AffineTransformType::OutputVectorType moffset;
moffset[0]=mpoint[0]*(-1);
moffset[1]=mpoint[1]*(-1);
AffineTransformType::OutputVectorType foffset;
foffset[0]=fpoint[0];
foffset[1]=fpoint[1];
AffineTransformType::Pointer affineTransformGroundTruth = AffineTransformType::New();
affineTransformGroundTruth->SetIdentity();
affineTransformGroundTruth->Translate(moffset);
affineTransformGroundTruth->Rotate2D(itk::Math::pi);
affineTransformGroundTruth->Translate(foffset);
/** define a resample filter that will ultimately be used to deform the image */
typedef itk::ResampleImageFilter<
InternalImageType,
InternalImageType > ResampleFilterType;
ResampleFilterType::Pointer resample = ResampleFilterType::New();
resample->SetTransform( affineTransformGroundTruth );
resample->SetInput( movingImage );
resample->SetSize( fixedImage->GetLargestPossibleRegion().GetSize() );
resample->SetOutputOrigin( fixedImage->GetOrigin() );
resample->SetOutputSpacing( fixedImage->GetSpacing() );
resample->SetOutputDirection( fixedImage->GetDirection() );
resample->SetDefaultPixelValue( 0 );
resample->Update();
AffineTransformType::Pointer affineTransform = AffineTransformType::New();
affineTransform->SetIdentity();
std::cout <<" affineTransform params prior to optimization " << affineTransform->GetParameters() << std::endl;
//identity transform for fixed image
typedef itk::IdentityTransform<double, Dimension> IdentityTransformType;
IdentityTransformType::Pointer identityTransform = IdentityTransformType::New();
identityTransform->SetIdentity();
// The metric
// typedef itk::MeanSquaresImageToImageMetricv4 < InternalImageType, InternalImageType >
typedef itk::CorrelationImageToImageMetricv4 < InternalImageType, InternalImageType >
// typedef itk::MattesMutualInformationImageToImageMetricv4 < InternalImageType, InternalImageType >
// typedef itk::JointHistogramMutualInformationImageToImageMetricv4 < InternalImageType, InternalImageType >
MetricType;
typedef MetricType::FixedSampledPointSetType PointSetType;
MetricType::Pointer metric = MetricType::New();
// metric->SetNumberOfHistogramBins(20);
typedef PointSetType::PointType PointType;
PointSetType::Pointer pset(PointSetType::New());
unsigned long ind=0,ct=0;
itk::ImageRegionIteratorWithIndex<InternalImageType> It(fixedImage, fixedImage->GetLargestPossibleRegion() );
for( It.GoToBegin(); !It.IsAtEnd(); ++It )
{
// take every N^th point
if ( ct % 20 == 0 )
{
PointType pt;
fixedImage->TransformIndexToPhysicalPoint( It.GetIndex(), pt);
pset->SetPoint(ind, pt);
ind++;
}
ct++;
}
metric->SetFixedSampledPointSet( pset );
metric->SetUseFixedSampledPointSet( true );
metric->SetFixedImage( fixedImage );
metric->SetMovingImage( movingImage );
if( rotateinput ) metric->SetMovingImage( resample->GetOutput() );
metric->SetFixedTransform( identityTransform );
metric->SetMovingTransform( affineTransform );
bool gaussian=false;
metric->SetUseMovingImageGradientFilter( gaussian );
metric->SetUseFixedImageGradientFilter( gaussian );
metric->Initialize();
typedef itk::RegistrationParameterScalesFromPhysicalShift< MetricType > RegistrationParameterScalesFromShiftType;
RegistrationParameterScalesFromShiftType::Pointer shiftScaleEstimator = RegistrationParameterScalesFromShiftType::New();
shiftScaleEstimator->SetMetric(metric);
typedef itk::GradientDescentOptimizerv4 OptimizerType;
OptimizerType::Pointer optimizer = OptimizerType::New();
optimizer->SetMetric( metric );
optimizer->SetNumberOfIterations( numberOfIterations );
optimizer->SetScalesEstimator( shiftScaleEstimator );
optimizer->SetMaximumStepSizeInPhysicalUnits( 1 );
optimizer->SetConvergenceWindowSize(20);
optimizer->SetMinimumConvergenceValue(-1.e-5);
typedef itk::MultiStartOptimizerv4 MOptimizerType;
MOptimizerType::Pointer MOptimizer = MOptimizerType::New();
MOptimizerType::ParametersListType parametersList = MOptimizer->GetParametersList();
float rotplus=10;
// for ( float i = 180; i <= 180; i+=rotplus )
for ( float i = 0; i < 360; i+=rotplus )
{
AffineTransformType::Pointer aff = AffineTransformType::New();
aff->SetIdentity();
float rad=(float)i*itk::Math::pi /180.0;
aff->Translate(moffset);
aff->Rotate2D(rad);
aff->Translate(foffset);
parametersList.push_back( aff->GetParameters() );
}
MOptimizer->SetMetric( metric );
MOptimizer->SetParametersList( parametersList );
MOptimizer->SetLocalOptimizer(optimizer);
MOptimizer->StartOptimization();
affineTransform->SetParameters(MOptimizer->GetBestParameters());
MOptimizerType::MetricValuesListType metlist=MOptimizer->GetMetricValuesList();
for (unsigned int i=0; i < metlist.size(); i++)
{
std::cout << " angle " << i*rotplus <<" energy " <<metlist[i] << std::endl;
}
std::cout << " best angle " << MOptimizer->GetBestParametersIndex()*rotplus << " energy " << metlist[ MOptimizer->GetBestParametersIndex() ] << std::endl;
std::cout <<" Done. Best parameters: " <<MOptimizer->GetBestParameters() << " index " << MOptimizer->GetBestParametersIndex() << std::endl;
std::cout <<" Ground truth parameters: " << affineTransformGroundTruth->GetParameters() << std::endl;
//warp the image with the displacement field
ResampleFilterType::Pointer resampleout = ResampleFilterType::New();
resampleout->SetTransform( affineTransform );
resampleout->SetInput( movingImage );
if ( rotateinput ) resampleout->SetInput( resample->GetOutput() );
resampleout->SetSize( fixedImage->GetLargestPossibleRegion().GetSize() );
resampleout->SetOutputOrigin( fixedImage->GetOrigin() );
resampleout->SetOutputSpacing( fixedImage->GetSpacing() );
resampleout->SetOutputDirection( fixedImage->GetDirection() );
resampleout->SetDefaultPixelValue( 0 );
resampleout->Update();
//write the warped image into a file
typedef itk::ImageFileWriter< InternalImageType > WriterType;
WriterType::Pointer writer = WriterType::New();
writer->SetFileName( argv[3] );
writer->SetInput( resampleout->GetOutput() );
writer->Update();
std::cout << "After optimization affine params are: " << affineTransform->GetParameters() << std::endl;
if ( MOptimizer->GetBestParametersIndex() == 18 ) return EXIT_SUCCESS;
else return EXIT_FAILURE;
}
|
