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
|
/*=========================================================================
Copyright (c) Kitware, Inc.
All rights reserved.
See Copyright.txt or http://www.kitware.com/VolViewCopyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notice for more information.
=========================================================================*/
/** This module refines the labeling of an image by applying iterations of a
* MarkovRandomField filter. The module expects two inputs, the first one is
* the current labeling of the image, the second one is the original image from
* which the labeling was generated. */
#ifndef _vvITKMarkovRandomField_h
#define _vvITKMarkovRandomField_h
#include "vvITKFilterModuleTwoInputs.h"
#include "itkImage.h"
#include "itkFixedArray.h"
#include "itkScalarToArrayCastImageFilter.h"
#include "itkMRFImageFilter.h"
#include "itkDistanceToCentroidMembershipFunction.h"
#include "itkMinimumDecisionRule.h"
#include "itkImageClassifierBase.h"
namespace VolView
{
namespace PlugIn
{
template< class TInputPixelType >
class MarkovRandomField : public
FilterModuleTwoInputs<
itk::MRFImageFilter<
itk::Image< itk::FixedArray<TInputPixelType,1>, 3 >,
itk::Image<unsigned char,3> >,
itk::Image<unsigned char,3>,
itk::Image<TInputPixelType,3> > {
public:
typedef itk::Image<unsigned char,3> LabelImageType;
typedef itk::Image<TInputPixelType,3> InputImageType;
typedef itk::FixedArray<TInputPixelType,1> ArrayPixelType;
typedef itk::Image< ArrayPixelType, 3 > ArrayImageType;
typedef itk::MRFImageFilter< ArrayImageType,
LabelImageType > MRFFilterType;
typedef FilterModuleTwoInputs< MRFFilterType,
LabelImageType,
InputImageType > Superclass;
typedef typename MRFFilterType::OutputImageType OutputImageType;
typedef typename OutputImageType::PixelType OutputPixelType;
typedef itk::ScalarToArrayCastImageFilter<
InputImageType,
ArrayImageType > ScalarToArrayFilterType;
public:
/** Constructor */
MarkovRandomField()
{
}
/** Destructor */
virtual ~MarkovRandomField()
{
}
/** ProcessData performs the actual filtering on the data.
In this class, this method only initialize the import
filter for the second input, then it lets the ProcessData
method of the base class perform the rest of the operations. */
void
ProcessData( const vtkVVProcessDataStruct * pds )
{
// Let superclass perform initial connections
this->Superclass::ProcessData( pds );
MRFFilterType * filter = this->GetFilter();
vtkVVPluginInfo *info = this->GetPluginInfo();
const unsigned int neighborhoodRadius = atoi( info->GetGUIProperty(info, 0, VVP_GUI_VALUE ));
const unsigned int numberOfClasses = atoi( info->GetGUIProperty(info, 1, VVP_GUI_VALUE ));
const unsigned int maximumNumberOfIterations = atoi( info->GetGUIProperty(info, 2, VVP_GUI_VALUE ));
const float smoothingFactor = atof( info->GetGUIProperty(info, 3, VVP_GUI_VALUE ));
const float errorTolerance = atof( info->GetGUIProperty(info, 4, VVP_GUI_VALUE ));
filter->SetNeighborhoodRadius( neighborhoodRadius );
filter->SetNumberOfClasses( numberOfClasses );
filter->SetMaximumNumberOfIterations( maximumNumberOfIterations );
filter->SetSmoothingFactor( smoothingFactor );
filter->SetErrorTolerance( errorTolerance );
typename ScalarToArrayFilterType::Pointer
scalarToArrayFilter = ScalarToArrayFilterType::New();
scalarToArrayFilter->SetInput( this->GetInput2() );
scalarToArrayFilter->ReleaseDataFlagOn();
filter->SetInput( scalarToArrayFilter->GetOutput() );
typedef itk::ImageClassifierBase<
ArrayImageType,
LabelImageType > SupervisedClassifierType;
typedef typename SupervisedClassifierType::Pointer ClassifierPointer;
ClassifierPointer classifier = SupervisedClassifierType::New();
typedef itk::MinimumDecisionRule DecisionRuleType;
typedef typename DecisionRuleType::Pointer DecisionRulePointer;
DecisionRulePointer classifierDecisionRule = DecisionRuleType::New();
classifier->SetDecisionRule( classifierDecisionRule.GetPointer() );
typedef itk::Statistics::DistanceToCentroidMembershipFunction<
ArrayPixelType >
MembershipFunctionType;
typedef typename MembershipFunctionType::Pointer MembershipFunctionPointer;
vnl_vector<double> centroid(1);
for( unsigned int i=0; i < numberOfClasses; i++ )
{
MembershipFunctionPointer membershipFunction =
MembershipFunctionType::New();
centroid[0] = 0.0; // FIXME : PUT HERE THE MEAN FOR CLASS ITH
membershipFunction->SetCentroid( centroid );
classifier->AddMembershipFunction( membershipFunction );
}
filter->SetClassifier( classifier );
// Execute the filter
try
{
filter->Update();
}
catch( itk::ProcessAborted & )
{
return;
}
// Copy the data (with casting) to the output buffer provided by the PlugIn API
typename OutputImageType::ConstPointer outputImage = filter->GetOutput();
typedef itk::ImageRegionConstIterator< OutputImageType > OutputIteratorType;
OutputIteratorType ot( outputImage, outputImage->GetBufferedRegion() );
typedef unsigned char OutputVolumePixelType;
OutputVolumePixelType * outData = (OutputVolumePixelType *)(pds->outData);
ot.GoToBegin();
while( !ot.IsAtEnd() )
{
*outData = static_cast<unsigned char>( ( ot.Get() ) );
++ot;
++outData;
}
} // end of ProcessData
private:
};
} // end namespace PlugIn
} // end namespace VolView
#endif
|
