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
|
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkHessian3DToVesselnessMeasureImageFilter.txx,v $
Language: C++
Date: $Date: 2008-01-19 19:50:01 $
Version: $Revision: 1.6 $
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 _itkHessian3DToVesselnessMeasureImageFilter_txx
#define _itkHessian3DToVesselnessMeasureImageFilter_txx
#include "itkHessian3DToVesselnessMeasureImageFilter.h"
#include "itkImageRegionIterator.h"
#include "itkImageRegionConstIterator.h"
#include "vnl/vnl_math.h"
namespace itk
{
/**
* Constructor
*/
template < typename TPixel >
Hessian3DToVesselnessMeasureImageFilter< TPixel >
::Hessian3DToVesselnessMeasureImageFilter()
{
m_Alpha1 = 0.5;
m_Alpha2 = 2.0;
// Hessian( Image ) = Jacobian( Gradient ( Image ) ) is symmetric
m_SymmetricEigenValueFilter = EigenAnalysisFilterType::New();
m_SymmetricEigenValueFilter->SetDimension( ImageDimension );
m_SymmetricEigenValueFilter->OrderEigenValuesBy(
EigenAnalysisFilterType::FunctorType::OrderByValue );
}
template < typename TPixel >
void
Hessian3DToVesselnessMeasureImageFilter< TPixel >
::GenerateData()
{
itkDebugMacro(<< "Hessian3DToVesselnessMeasureImageFilter generating data ");
m_SymmetricEigenValueFilter->SetInput( this->GetInput() );
typename OutputImageType::Pointer output = this->GetOutput();
typedef typename EigenAnalysisFilterType::OutputImageType
EigenValueOutputImageType;
m_SymmetricEigenValueFilter->Update();
const typename EigenValueOutputImageType::ConstPointer eigenImage =
m_SymmetricEigenValueFilter->GetOutput();
// walk the region of eigen values and get the vesselness measure
EigenValueArrayType eigenValue;
ImageRegionConstIterator<EigenValueOutputImageType> it;
it = ImageRegionConstIterator<EigenValueOutputImageType>(
eigenImage, eigenImage->GetRequestedRegion());
ImageRegionIterator<OutputImageType> oit;
this->AllocateOutputs();
oit = ImageRegionIterator<OutputImageType>(output,
output->GetRequestedRegion());
oit.GoToBegin();
it.GoToBegin();
while (!it.IsAtEnd())
{
// Get the eigen value
eigenValue = it.Get();
// normalizeValue <= 0 for bright line structures
double normalizeValue = vnl_math_min( -1.0 * eigenValue[1], -1.0 * eigenValue[0]);
// Similarity measure to a line structure
if( normalizeValue > 0 )
{
double lineMeasure;
if( eigenValue[2] <= 0 )
{
lineMeasure =
vcl_exp(-0.5 * vnl_math_sqr( eigenValue[2] / (m_Alpha1 * normalizeValue)));
}
else
{
lineMeasure =
vcl_exp(-0.5 * vnl_math_sqr( eigenValue[2] / (m_Alpha2 * normalizeValue)));
}
lineMeasure *= normalizeValue;
oit.Set( static_cast< OutputPixelType >(lineMeasure) );
}
else
{
oit.Set( NumericTraits< OutputPixelType >::Zero );
}
++it;
++oit;
}
}
template < typename TPixel >
void
Hessian3DToVesselnessMeasureImageFilter< TPixel >
::PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Alpha1: " << m_Alpha1 << std::endl;
os << indent << "Alpha2: " << m_Alpha2 << std::endl;
}
} // end namespace itk
#endif
|
