File: itkHessian3DToVesselnessMeasureImageFilterTest.cxx

package info (click to toggle)
insighttoolkit5 5.4.3-5
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid, trixie
  • size: 704,384 kB
  • sloc: cpp: 783,592; ansic: 628,724; xml: 44,704; fortran: 34,250; python: 22,874; sh: 4,078; pascal: 2,636; lisp: 2,158; makefile: 464; yacc: 328; asm: 205; perl: 203; lex: 146; tcl: 132; javascript: 98; csh: 81
file content (162 lines) | stat: -rw-r--r-- 4,710 bytes parent folder | download
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
/*=========================================================================
 *
 *  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.
 *
 *=========================================================================*/

#include "itkHessianRecursiveGaussianImageFilter.h"
#include "itkHessian3DToVesselnessMeasureImageFilter.h"
#include "itkTestingMacros.h"


int
itkHessian3DToVesselnessMeasureImageFilterTest(int argc, char * argv[])
{
  if (argc != 4)
  {
    std::cerr << "Missing parameters." << std::endl;
    std::cerr << "Usage: " << itkNameOfTestExecutableMacro(argv);
    std::cerr << " sigma alpha1 alpha2" << std::endl;
    return EXIT_FAILURE;
  }

  // Define the dimension of the images
  constexpr unsigned int myDimension = 3;

  // Declare the types of the images
  using myImageType = itk::Image<float, myDimension>;

  // Declare the type of the index to access images
  using myIndexType = itk::Index<myDimension>;

  // Declare the type of the size
  using mySizeType = itk::Size<myDimension>;

  // Declare the type of the Region
  using myRegionType = itk::ImageRegion<myDimension>;

  // Create the image
  auto inputImage = myImageType::New();


  // Define their size, and start index
  mySizeType size;
  size[0] = 8;
  size[1] = 8;
  size[2] = 8;

  myIndexType start;
  start.Fill(0);

  myRegionType region{ start, size };

  // Initialize Image A
  inputImage->SetRegions(region);
  inputImage->Allocate();

  // Declare Iterator type for the input image
  using myIteratorType = itk::ImageRegionIteratorWithIndex<myImageType>;

  // Create one iterator for the Input Image A (this is a light object)
  myIteratorType it(inputImage, inputImage->GetRequestedRegion());

  // Initialize the content of Image A
  while (!it.IsAtEnd())
  {
    it.Set(0.0);
    ++it;
  }

  size[0] = 1;
  size[1] = 8;
  size[2] = 1;

  start[0] = 3;
  start[1] = 0;
  start[2] = 3;

  // Create one iterator for an internal region
  region.SetSize(size);
  region.SetIndex(start);
  myIteratorType itb(inputImage, region);

  // Initialize the content the internal region
  while (!itb.IsAtEnd())
  {
    itb.Set(100.0);
    ++itb;
  }

  // Declare the type for the Hessian filter
  using myHessianFilterType = itk::HessianRecursiveGaussianImageFilter<myImageType>;

  // Declare the type for the vesselness filter
  using myVesselnessFilterType = itk::Hessian3DToVesselnessMeasureImageFilter<float>;

  using myVesselnessImageType = myVesselnessFilterType::OutputImageType;


  // Create a Hessian Filter
  auto filterHessian = myHessianFilterType::New();

  // Create a vesselness Filter
  auto filterVesselness = myVesselnessFilterType::New();

  ITK_EXERCISE_BASIC_OBJECT_METHODS(filterVesselness, Hessian3DToVesselnessMeasureImageFilter, ImageToImageFilter);


  // Connect the input images
  filterHessian->SetInput(inputImage);
  filterVesselness->SetInput(filterHessian->GetOutput());

  // Select the value of Sigma
  auto sigma = static_cast<typename myHessianFilterType::RealType>(std::stod(argv[1]));
  filterHessian->SetSigma(sigma);

  auto alpha1 = std::stod(argv[2]);
  filterVesselness->SetAlpha1(alpha1);
  ITK_TEST_SET_GET_VALUE(alpha1, filterVesselness->GetAlpha1());

  auto alpha2 = std::stod(argv[3]);
  filterVesselness->SetAlpha2(alpha2);
  ITK_TEST_SET_GET_VALUE(alpha2, filterVesselness->GetAlpha2());

  // Execute the filter
  filterVesselness->Update();

  // Get the Smart Pointer to the Filter Output
  // It is important to do it AFTER the filter is Updated
  // Because the object connected to the output may be changed
  // by another during GenerateData() call
  myVesselnessImageType::Pointer outputImage = filterVesselness->GetOutput();

  // Declare Iterator type for the output image
  using myOutputIteratorType = itk::ImageRegionIteratorWithIndex<myVesselnessImageType>;

  // Create an iterator for going through the output image
  myOutputIteratorType itg(outputImage, outputImage->GetRequestedRegion());

  // Print the content of the result image
  std::cout << " Result " << std::endl;
  itg.GoToBegin();
  while (!itg.IsAtEnd())
  {
    std::cout << itg.Get() << ' ';
    ++itg;
  }


  return EXIT_SUCCESS;
}