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 ===========================================================================**/
19 //--------------------------------------------------------------------
20 template <class ImageType>
21 clitk::RelativePositionAnalyzerFilter<ImageType>::
22 RelativePositionAnalyzerFilter():
23 itk::ImageToImageFilter<ImageType, ImageType>()
25 this->SetNumberOfRequiredInputs(3); // Input : support, object, target
26 SetBackgroundValue(0);
27 SetForegroundValue(1);
29 SetAreaLossTolerance(0.01);
32 SetSizeWithThreshold(0);
33 SetSizeWithReverseThreshold(0);
35 //--------------------------------------------------------------------
38 //--------------------------------------------------------------------
39 template <class ImageType>
41 clitk::RelativePositionAnalyzerFilter<ImageType>::
42 SetInputSupport(const ImageType * image)
44 // Process object is not const-correct so the const casting is required.
45 this->SetNthInput(0, const_cast<ImageType *>(image));
47 //--------------------------------------------------------------------
50 //--------------------------------------------------------------------
51 template <class ImageType>
53 clitk::RelativePositionAnalyzerFilter<ImageType>::
54 SetInputObject(const ImageType * image)
56 // Process object is not const-correct so the const casting is required.
57 this->SetNthInput(1, const_cast<ImageType *>(image));
59 //--------------------------------------------------------------------
62 //--------------------------------------------------------------------
63 template <class ImageType>
65 clitk::RelativePositionAnalyzerFilter<ImageType>::
66 SetInputTarget(const ImageType * image)
68 // Process object is not const-correct so the const casting is required.
69 this->SetNthInput(2, const_cast<ImageType *>(image));
71 //--------------------------------------------------------------------
74 //--------------------------------------------------------------------
75 template <class ImageType>
77 clitk::RelativePositionAnalyzerFilter<ImageType>::
82 //--------------------------------------------------------------------
85 //--------------------------------------------------------------------
86 template <class ImageType>
88 clitk::RelativePositionAnalyzerFilter<ImageType>::
89 GenerateOutputInformation()
91 ImagePointer input = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(0));
92 ImagePointer outputImage = this->GetOutput(0);
93 outputImage->SetRegions(outputImage->GetLargestPossibleRegion());
95 //--------------------------------------------------------------------
98 //--------------------------------------------------------------------
99 template <class ImageType>
101 clitk::RelativePositionAnalyzerFilter<ImageType>::
104 ImagePointer temp = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(0));
105 m_Object = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(1));
106 m_Target = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(2));
108 // Remove object from support (keep initial image)
109 m_Support = clitk::Clone<ImageType>(temp);
110 clitk::AndNot<ImageType>(m_Support, m_Object, GetBackgroundValue());
112 // Define filter to compute statics on mask image
113 typedef itk::LabelStatisticsImageFilter<ImageType, ImageType> StatFilterType;
114 typename StatFilterType::Pointer statFilter = StatFilterType::New();
116 // Compute the initial support size
117 statFilter->SetInput(m_Support);
118 statFilter->SetLabelInput(m_Support);
119 statFilter->Update();
120 SetSupportSize(statFilter->GetCount(GetForegroundValue()));
121 // DD(GetSupportSize());
123 // Compute the initial target size
124 ImagePointer s = clitk::ResizeImageLike<ImageType>(m_Support, m_Target, GetBackgroundValue());
125 statFilter->SetInput(s);
126 statFilter->SetLabelInput(m_Target);
127 statFilter->Update();
128 SetTargetSize(statFilter->GetCount(GetForegroundValue()));
129 // DD(GetTargetSize());
132 int bins = GetNumberOfBins();
133 double tolerance = GetAreaLossTolerance();
136 double angle = GetDirection().angle1;
137 typename FloatImageType::Pointer map = ComputeFuzzyMap(m_Object, m_Target, m_Support, angle);
138 writeImage<FloatImageType>(map, "fuzzy_"+toString(clitk::rad2deg(angle))+".mha");
140 // Compute the optimal thresholds (direct and inverse)
141 double mThreshold=0.0;
142 double mReverseThreshold=1.0;
143 ComputeOptimalThresholds(map, m_Target, bins, tolerance, mThreshold, mReverseThreshold);
145 // Use the threshold to compute new support
146 int s1 = GetSupportSize();
147 if (mThreshold > 0.0) {
148 ImagePointer support1 =
149 clitk::SliceBySliceRelativePosition<ImageType>(m_Support, m_Object, 2,
151 angle,false, // inverseFlag
152 false, // uniqueConnectedComponent
154 false);//singleObjectCCL
155 // Compute the new support size
156 statFilter->SetInput(support1);
157 statFilter->SetLabelInput(support1);
158 statFilter->Update();
159 s1 = statFilter->GetCount(GetForegroundValue());
162 int s2 = GetSupportSize();
163 if (mReverseThreshold < 1.0) {
164 ImagePointer support2 =
165 clitk::SliceBySliceRelativePosition<ImageType>(m_Support, m_Object, 2,
167 angle,true,// inverseFlag
168 false, // uniqueConnectedComponent
170 false); //singleObjectCCL
171 // Compute the new support size
172 statFilter = StatFilterType::New();
173 statFilter->SetInput(support2);
174 statFilter->SetLabelInput(support2);
175 statFilter->Update();
176 s2 = statFilter->GetCount(GetForegroundValue());
179 // Set results values
180 m_Info.threshold = mThreshold;
181 m_Info.sizeAfterThreshold = s1;
182 m_Info.sizeBeforeThreshold = GetSupportSize();
183 m_Info.sizeReference = GetTargetSize();
184 m_InfoReverse.threshold = mReverseThreshold;
185 m_InfoReverse.sizeAfterThreshold = s2;
186 m_InfoReverse.sizeBeforeThreshold = GetSupportSize();
187 m_InfoReverse.sizeReference = GetTargetSize();
189 //--------------------------------------------------------------------
192 //--------------------------------------------------------------------
193 template <class ImageType>
194 typename clitk::RelativePositionAnalyzerFilter<ImageType>::FloatImageType::Pointer
195 clitk::RelativePositionAnalyzerFilter<ImageType>::
196 ComputeFuzzyMap(ImageType * object, ImageType * target, ImageType * support, double angle)
198 typedef clitk::SliceBySliceRelativePositionFilter<ImageType> SliceRelPosFilterType;
199 typedef typename SliceRelPosFilterType::FloatImageType FloatImageType;
200 typename SliceRelPosFilterType::Pointer sliceRelPosFilter = SliceRelPosFilterType::New();
201 sliceRelPosFilter->VerboseStepFlagOff();
202 sliceRelPosFilter->WriteStepFlagOff();
203 sliceRelPosFilter->SetInput(support);
204 sliceRelPosFilter->SetInputObject(object);
205 sliceRelPosFilter->SetDirection(2);
206 sliceRelPosFilter->SetIntermediateSpacingFlag(false);
207 //sliceRelPosFilter->AddOrientationTypeString(orientation);
208 sliceRelPosFilter->AddAnglesInRad(angle, 0.0);
209 sliceRelPosFilter->FuzzyMapOnlyFlagOn(); // do not threshold, only compute the fuzzy map
210 // sliceRelPosFilter->PrintOptions();
211 sliceRelPosFilter->Update();
212 typename FloatImageType::Pointer map = sliceRelPosFilter->GetFuzzyMap();
214 // Resize map like object to allow SetBackground
215 map = clitk::ResizeImageLike<FloatImageType>(map, object, GetBackgroundValue());
217 // Remove initial object from the fuzzy map
218 map = clitk::SetBackground<FloatImageType, ImageType>(map, object, GetForegroundValue(), 0.0, true);
220 // Resize the fuzzy map like the target, put 2.0 when outside
221 map = clitk::ResizeImageLike<FloatImageType>(map, target, 2.0); // Put 2.0 when out of initial map
226 //--------------------------------------------------------------------
229 //--------------------------------------------------------------------
230 template <class ImageType>
232 clitk::RelativePositionAnalyzerFilter<ImageType>::
233 ComputeOptimalThresholds(FloatImageType * map, ImageType * target, int bins, double tolerance,
234 double & threshold, double & reverseThreshold)
236 // Get the histogram of fuzzy values inside the target image
237 typedef itk::LabelStatisticsImageFilter<FloatImageType, ImageType> FloatStatFilterType;
238 typename FloatStatFilterType::Pointer f = FloatStatFilterType::New();
240 f->SetLabelInput(target);
241 f->UseHistogramsOn();
242 f->SetHistogramParameters(bins, 0.0, 1.1);
244 int count = f->GetCount(GetForegroundValue());
245 typename FloatStatFilterType::HistogramPointer h = f->GetHistogram(GetForegroundValue());
247 // Debug : dump histogram
249 std::ofstream histogramFile(std::string("fuzzy_histo_"+toString(i)+".txt").c_str());
250 for(int j=0; j<bins; j++) {
251 histogramFile << h->GetMeasurement(j,0)
252 << "\t" << h->GetFrequency(j)
253 << "\t" << (double)h->GetFrequency(j)/(double)count << std::endl;
255 histogramFile.close();
258 // Analyze the histogram (direct)
262 for(int j=0; j<bins; j++) {
263 sum += ((double)h->GetFrequency(j)/(double)count);
264 if ((!found) && (sum > tolerance)) {
265 if (j==0) threshold = h->GetBinMin(0,j);
266 else threshold = h->GetBinMin(0,j-1); // the last before reaching the threshold
271 // Analyze the histogram (reverse)
274 reverseThreshold = 1.0;
275 for(int j=bins-1; j>=0; j--) {
276 sum += ((double)h->GetFrequency(j)/(double)count);
277 if ((!found) && (sum > tolerance)) {
278 if (j==bins-1) reverseThreshold = h->GetBinMax(0,j);
279 else reverseThreshold = h->GetBinMax(0,j+1);
284 //--------------------------------------------------------------------