forked from InsightSoftwareConsortium/ITK
-
Notifications
You must be signed in to change notification settings - Fork 0
/
itkShapeDetectionLevelSetFunction.h
141 lines (119 loc) · 5.22 KB
/
itkShapeDetectionLevelSetFunction.h
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
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkShapeDetectionLevelSetFunction.h
Language: C++
Date: $Date$
Version: $Revision$
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 __itkShapeDetectionLevelSetFunction_h_
#define __itkShapeDetectionLevelSetFunction_h_
#include "itkSegmentationLevelSetFunction.h"
namespace itk {
/** \class ShapeDetectionLevelSetFunction
*
* \brief This function is used in the ShapeDetectionLevelSetImageFilter to
* segment structures in an image based on a user supplied edge potential map.
*
* \par IMPORTANT
* The LevelSetFunction class contain additional information necessary
* to gain full understanding of how to use this function.
*
* ShapeDetectionLevelSetFunction is a subclass of the generic LevelSetFunction.
* It is used to segment structures in an image based on a user supplied
* edge potential map \f$ g(I) \f$, which
* has values close to zero in regions near edges (or high image gradient) and values
* close to one in regions with relatively constant intensity. Typically, the edge
* potential map is a function of the image gradient, for example:
*
* \f[ g(I) = 1 / ( 1 + | (\nabla * G)(I)| ) \f]
* \f[ g(I) = \exp^{-|(\nabla * G)(I)|} \f]
*
* where \f$ I \f$ is image intensity and
* \f$ (\nabla * G) \f$ is the derivative of Gaussian operator.
*
* The edge potential image is set via the SetFeatureImage() method.
*
* In this function both the propagation term \f$ P(\mathbf{x}) \f$
* and the curvature spatial modifier term \f$ Z(\mathbf{x}) \f$ are taken directly
* from the edge potential image such that:
*
* \f[ P(\mathbf{x}) = g(\mathbf{x}) \f]
* \f[ Z(\mathbf{x}) = g(\mathbf{x}) \f]
*
* Note that there is no advection term in this function.
*
* This implementation is based on:
* "Shape Modeling with Front Propagation: A Level Set Approach",
* R. Malladi, J. A. Sethian and B. C. Vermuri.
* IEEE Trans. on Pattern Analysis and Machine Intelligence,
* Vol 17, No. 2, pp 158-174, February 1995
*
* \sa LevelSetFunction
* \sa SegmentationLevelSetImageFunction
* \sa ShapeDetectionLevelSetImageFilter
*
* \ingroup FiniteDifferenceFunctions
*/
template <class TImageType, class TFeatureImageType = TImageType>
class ITK_EXPORT ShapeDetectionLevelSetFunction
: public SegmentationLevelSetFunction<TImageType, TFeatureImageType>
{
public:
/** Standard class typedefs. */
typedef ShapeDetectionLevelSetFunction Self;
typedef SegmentationLevelSetFunction<TImageType, TFeatureImageType> Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
typedef TFeatureImageType FeatureImageType;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods) */
itkTypeMacro( ShapeDetectionLevelSetFunction, SegmentationLevelSetFunction );
/** Extract some parameters from the superclass. */
typedef typename Superclass::ImageType ImageType;
typedef typename Superclass::NeighborhoodType NeighborhoodType;
typedef typename Superclass::ScalarValueType ScalarValueType;
typedef typename Superclass::FeatureScalarType FeatureScalarType;
typedef typename Superclass::RadiusType RadiusType;
typedef typename Superclass::FloatOffsetType FloatOffsetType;
typedef typename Superclass::GlobalDataStruct GlobalDataStruct;
/** Extract some parameters from the superclass. */
itkStaticConstMacro(ImageDimension, unsigned int,
Superclass::ImageDimension);
virtual void CalculateSpeedImage();
/** The curvature speed is same as the propagation speed. */
virtual ScalarValueType CurvatureSpeed(const NeighborhoodType & neighborhood,
const FloatOffsetType & offset, GlobalDataStruct *gd ) const
{ return PropagationSpeed( neighborhood, offset, gd ); }
virtual void Initialize(const RadiusType &r)
{
Superclass::Initialize(r);
this->SetAdvectionWeight( NumericTraits<ScalarValueType>::Zero );
this->SetPropagationWeight( NumericTraits<ScalarValueType>::One );
this->SetCurvatureWeight( NumericTraits<ScalarValueType>::One );
}
protected:
ShapeDetectionLevelSetFunction()
{
this->SetAdvectionWeight( NumericTraits<ScalarValueType>::Zero );
this->SetPropagationWeight( NumericTraits<ScalarValueType>::One );
this->SetCurvatureWeight( NumericTraits<ScalarValueType>::One );
}
virtual ~ShapeDetectionLevelSetFunction() {}
ShapeDetectionLevelSetFunction(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
void PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os, indent );
}
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkShapeDetectionLevelSetFunction.txx"
#endif
#endif