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
|
/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
/*=========================================================================
*
* Portions of this file are subject to the VTK Toolkit Version 3 copyright.
*
* Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
*
* For complete copyright, license and disclaimer of warranty information
* please refer to the NOTICE file at the top of the ITK source tree.
*
*=========================================================================*/
#ifndef itkLabelImageGaussianInterpolateImageFunction_hxx
#define itkLabelImageGaussianInterpolateImageFunction_hxx
namespace itk
{
template <typename TInputImage, typename TCoordRep, typename TPixelCompare>
auto
LabelImageGaussianInterpolateImageFunction<TInputImage, TCoordRep, TPixelCompare>::EvaluateAtContinuousIndex(
const ContinuousIndexType & cindex,
OutputType * itkNotUsed(grad)) const -> OutputType
{
vnl_vector<RealType> erfArray[ImageDimension];
vnl_vector<RealType> gerfArray[ImageDimension];
typename Superclass::RegionType region = this->ComputeInterpolationRegion(cindex);
// Compute the ERF difference arrays
for (unsigned int d = 0; d < ImageDimension; ++d)
{
this->ComputeErrorFunctionArray(region, d, cindex[d], erfArray[d], gerfArray[d], false);
}
RealType wmax = 0.0;
OutputType Vmax{};
// Create a map object to store weights for each label encountered
// inside the search region. This is not as efficient as having a
// linear list of labels, but probably not a huge deal compared to
// having to evaluate the erf function
using WeightMapType = std::map<OutputType, RealType, TPixelCompare>;
WeightMapType weightMap;
for (ImageRegionConstIteratorWithIndex<InputImageType> It(this->GetInputImage(), region); !It.IsAtEnd(); ++It)
{
unsigned int j = It.GetIndex()[0] - region.GetIndex()[0];
RealType w = erfArray[0][j];
for (unsigned int d = 1; d < ImageDimension; ++d)
{
j = It.GetIndex()[d] - region.GetIndex()[d];
w *= erfArray[d][j];
}
const OutputType V = It.Get();
auto it = weightMap.find(V);
RealType wtest = 0.0;
if (it != weightMap.end())
{
it->second += w;
wtest = it->second;
}
else
{
weightMap.insert(std::make_pair(V, w));
wtest = w;
}
// Keep track of the max value
if (wtest > wmax)
{
wmax = wtest;
Vmax = V;
}
}
return Vmax;
}
} // namespace itk
#endif
|
