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;
}
|