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
|
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkDoubleThresholdImageFilter.txx,v $
Language: C++
Date: $Date: 2006-08-01 19:16:17 $
Version: $Revision: 1.7 $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.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 notices for more information.
=========================================================================*/
#ifndef __itkDoubleThresholdImageFilter_txx
#define __itkDoubleThresholdImageFilter_txx
#include "itkDoubleThresholdImageFilter.h"
#include "itkReconstructionByDilationImageFilter.h"
#include "itkBinaryThresholdImageFilter.h"
#include "itkProgressAccumulator.h"
namespace itk {
template <class TInputImage, class TOutputImage>
DoubleThresholdImageFilter<TInputImage, TOutputImage>
::DoubleThresholdImageFilter()
: m_NumberOfIterationsUsed( 1 )
{
m_Threshold1 = NumericTraits<InputPixelType>::NonpositiveMin();
m_Threshold2 = NumericTraits<InputPixelType>::NonpositiveMin();
m_Threshold3 = NumericTraits<InputPixelType>::max();
m_Threshold4 = NumericTraits<InputPixelType>::max();
m_OutsideValue = NumericTraits<OutputPixelType>::Zero;
m_InsideValue = NumericTraits<OutputPixelType>::max();
m_FullyConnected = false;
}
template <class TInputImage, class TOutputImage>
void
DoubleThresholdImageFilter<TInputImage, TOutputImage>
::GenerateInputRequestedRegion()
{
// call the superclass' implementation of this method
Superclass::GenerateInputRequestedRegion();
// We need all the input.
InputImagePointer input = const_cast<InputImageType *>(this->GetInput());
if( input )
{
input->SetRequestedRegion( input->GetLargestPossibleRegion() );
}
}
template <class TInputImage, class TOutputImage>
void
DoubleThresholdImageFilter<TInputImage, TOutputImage>
::EnlargeOutputRequestedRegion(DataObject *)
{
this->GetOutput()
->SetRequestedRegion( this->GetOutput()->GetLargestPossibleRegion() );
}
template<class TInputImage, class TOutputImage>
void
DoubleThresholdImageFilter<TInputImage, TOutputImage>
::GenerateData()
{
// Allocate the output
this->AllocateOutputs();
// Build a mini-pipeline that involves two thresholds filters and a
// geodesic dilation.
typedef BinaryThresholdImageFilter<TInputImage, TOutputImage> ThresholdFilterType;
typedef ReconstructionByDilationImageFilter<TOutputImage, TOutputImage> DilationFilterType;
typename ThresholdFilterType::Pointer narrowThreshold = ThresholdFilterType::New();
// Create a process accumulator for tracking the progress of this minipipeline
ProgressAccumulator::Pointer progress = ProgressAccumulator::New();
progress->SetMiniPipelineFilter(this);
narrowThreshold->SetLowerThreshold( m_Threshold2 );
narrowThreshold->SetUpperThreshold( m_Threshold3 );
narrowThreshold->SetInsideValue( m_InsideValue );
narrowThreshold->SetOutsideValue( m_OutsideValue );
narrowThreshold->SetInput( this->GetInput() );
typename ThresholdFilterType::Pointer wideThreshold = ThresholdFilterType::New();
wideThreshold->SetLowerThreshold( m_Threshold1 );
wideThreshold->SetUpperThreshold( m_Threshold4 );
wideThreshold->SetInsideValue( m_InsideValue );
wideThreshold->SetOutsideValue( m_OutsideValue );
wideThreshold->SetInput( this->GetInput() );
typename DilationFilterType::Pointer dilate = DilationFilterType::New();
dilate->SetMarkerImage( narrowThreshold->GetOutput() );
dilate->SetMaskImage( wideThreshold->GetOutput() );
dilate->SetFullyConnected( m_FullyConnected );
//dilate->RunOneIterationOff(); // run to convergence
progress->RegisterInternalFilter(narrowThreshold,.1f);
progress->RegisterInternalFilter(wideThreshold,.1f);
progress->RegisterInternalFilter(dilate,.8f);
// graft our output to the dilate filter to force the proper regions
// to be generated
dilate->GraftOutput( this->GetOutput() );
// reconstruction by dilation
dilate->Update();
// graft the output of the dilate filter back onto this filter's
// output. this is needed to get the appropriate regions passed
// back.
this->GraftOutput( dilate->GetOutput() );
}
template<class TInputImage, class TOutputImage>
void
DoubleThresholdImageFilter<TInputImage, TOutputImage>
::PrintSelf(std::ostream &os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Threshold1: "
<< static_cast<typename NumericTraits<InputPixelType>::PrintType>(m_Threshold1)
<< std::endl;
os << indent << "Threshold2: "
<< static_cast<typename NumericTraits<InputPixelType>::PrintType>(m_Threshold2)
<< std::endl;
os << indent << "Threshold3: "
<< static_cast<typename NumericTraits<InputPixelType>::PrintType>(m_Threshold3)
<< std::endl;
os << indent << "Threshold4: "
<< static_cast<typename NumericTraits<InputPixelType>::PrintType>(m_Threshold4)
<< std::endl;
os << indent << "InsideValue: "
<< static_cast<typename NumericTraits<OutputPixelType>::PrintType>(m_InsideValue)
<< std::endl;
os << indent << "OutsideValue: "
<< static_cast<typename NumericTraits<OutputPixelType>::PrintType>(m_OutsideValue)
<< std::endl;
os << indent << "Number of iterations used to produce current output: "
<< m_NumberOfIterationsUsed << std::endl;
os << indent << "FullyConnected: " << m_FullyConnected << std::endl;
}
}// end namespace itk
#endif
|
