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/*=========================================================================
*
* 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 "itkGTest.h"
#include "itkImageFileReader.h"
#include "itkPipelineMonitorImageFilter.h"
#include "itkLabelOverlapMeasuresImageFilter.h"
namespace
{
class LabelOverlapMeasuresImageFilterFixture : public ::testing::Test
{
public:
LabelOverlapMeasuresImageFilterFixture() = default;
~LabelOverlapMeasuresImageFilterFixture() override = default;
protected:
template <unsigned int D, typename TPixelType = unsigned short>
struct FixtureUtilities
{
static const unsigned int Dimension = D;
using PixelType = TPixelType;
using ImageType = itk::Image<PixelType, Dimension>;
using IndexType = typename ImageType::IndexType;
using SourceType = itk::ImageSource<ImageType>;
using FilterType = itk::LabelOverlapMeasuresImageFilter<ImageType>;
static typename ImageType::Pointer
CreateImage(PixelType fillValue = PixelType{})
{
auto image = ImageType::New();
typename ImageType::SizeType imageSize;
imageSize.Fill(m_ImageSize);
typename ImageType::RegionType region(imageSize);
image->SetRegions(region);
image->Allocate();
image->FillBuffer(fillValue);
return image;
}
};
using Utils = FixtureUtilities<3, unsigned char>;
static const itk::SizeValueType m_ImageSize{ 128 };
};
} // namespace
TEST_F(LabelOverlapMeasuresImageFilterFixture, test0)
{
auto source = Utils::CreateImage(0);
auto target = Utils::CreateImage(0);
auto filter = Utils::FilterType::New();
filter->SetSourceImage(source);
filter->SetTargetImage(target);
filter->Update();
using RealType = Utils::FilterType::RealType;
EXPECT_EQ(filter->GetTotalOverlap(), itk::NumericTraits<RealType>::max());
EXPECT_EQ(filter->GetUnionOverlap(), itk::NumericTraits<RealType>::max());
EXPECT_EQ(filter->GetMeanOverlap(), itk::NumericTraits<RealType>::infinity());
EXPECT_EQ(filter->GetVolumeSimilarity(), itk::NumericTraits<RealType>::max());
EXPECT_EQ(filter->GetFalseNegativeError(), itk::NumericTraits<RealType>::max());
EXPECT_EQ(filter->GetFalsePositiveError(), itk::NumericTraits<RealType>::max());
EXPECT_EQ(filter->GetFalseDiscoveryRate(), itk::NumericTraits<RealType>::max());
}
TEST_F(LabelOverlapMeasuresImageFilterFixture, test1)
{
auto source = Utils::CreateImage(0);
auto target = Utils::CreateImage(0);
auto idx1 = itk::MakeFilled<Utils::IndexType>(1);
source->SetPixel(idx1, 1);
target->SetPixel(idx1, 1);
auto filter = Utils::FilterType::New();
filter->SetSourceImage(source);
filter->SetTargetImage(target);
filter->Update();
EXPECT_NEAR(filter->GetTotalOverlap(), 1, 0.0);
EXPECT_NEAR(filter->GetUnionOverlap(), 1, 0.0);
EXPECT_NEAR(filter->GetMeanOverlap(), 1, 0.0);
EXPECT_NEAR(filter->GetDiceCoefficient(), 1, 0.0);
EXPECT_NEAR(filter->GetVolumeSimilarity(), 0, 0.0);
EXPECT_NEAR(filter->GetFalseNegativeError(), 0, 0.0);
EXPECT_NEAR(filter->GetFalsePositiveError(), 0, 0.0);
EXPECT_NEAR(filter->GetFalseDiscoveryRate(), 0, 0.0);
}
TEST_F(LabelOverlapMeasuresImageFilterFixture, test2)
{
auto source = Utils::CreateImage(0);
auto target = Utils::CreateImage(0);
auto idx1 = itk::MakeFilled<Utils::IndexType>(1);
source->SetPixel(idx1, 1);
target->SetPixel(idx1, 1);
++idx1[0];
target->SetPixel(idx1, 1);
auto filter = Utils::FilterType::New();
filter->SetSourceImage(source);
filter->SetTargetImage(target);
filter->Update();
EXPECT_NEAR(filter->GetTotalOverlap(), 0.5, 0.0);
EXPECT_NEAR(filter->GetUnionOverlap(), 0.5, 0.0);
EXPECT_NEAR(filter->GetMeanOverlap(), 2.0 / 3.0, 1e-15);
EXPECT_NEAR(filter->GetDiceCoefficient(), 2.0 / 3.0, 1e-15);
EXPECT_NEAR(filter->GetVolumeSimilarity(), -2.0 / 3.0, 1e-15);
EXPECT_NEAR(filter->GetFalseNegativeError(), 0.5, 0.0);
EXPECT_NEAR(filter->GetFalsePositiveError(), 0, 0.0);
EXPECT_NEAR(filter->GetFalseDiscoveryRate(), 0, 0.0);
EXPECT_NEAR(filter->GetTargetOverlap(1), 0.5, 0.0);
EXPECT_NEAR(filter->GetUnionOverlap(1), 0.5, 0.0);
EXPECT_NEAR(filter->GetMeanOverlap(1), 2.0 / 3.0, 1e-15);
EXPECT_NEAR(filter->GetDiceCoefficient(1), 2.0 / 3.0, 1e-15);
EXPECT_NEAR(filter->GetVolumeSimilarity(1), -2.0 / 3.0, 1e-15);
EXPECT_NEAR(filter->GetFalseNegativeError(1), 0.5, 0.0);
EXPECT_NEAR(filter->GetFalsePositiveError(1), 0, 0.0);
EXPECT_NEAR(filter->GetFalseDiscoveryRate(1), 0, 0.0);
}
TEST_F(LabelOverlapMeasuresImageFilterFixture, test3)
{
auto source = Utils::CreateImage(0);
auto target = Utils::CreateImage(0);
auto idx1 = itk::MakeFilled<Utils::IndexType>(1);
source->SetPixel(idx1, 1);
target->SetPixel(idx1, 1);
++idx1[0];
target->SetPixel(idx1, 1);
auto idx2 = itk::MakeFilled<Utils::IndexType>(3);
source->SetPixel(idx2, 2);
target->SetPixel(idx2, 2);
++idx2[2];
source->SetPixel(idx2, 2);
target->SetPixel(idx2, 2);
++idx2[2];
source->SetPixel(idx2, 2);
++idx2[2];
auto filter = Utils::FilterType::New();
filter->SetSourceImage(source);
filter->SetTargetImage(target);
filter->Update();
EXPECT_NEAR(filter->GetTotalOverlap(), 0.75, 1e-15);
EXPECT_NEAR(filter->GetUnionOverlap(), 3.0 / 5.0, 1e-15);
EXPECT_NEAR(filter->GetMeanOverlap(), 0.75, 1e-15);
EXPECT_NEAR(filter->GetDiceCoefficient(), 0.75, 1e-15);
EXPECT_NEAR(filter->GetVolumeSimilarity(), 0, 1e-15);
EXPECT_NEAR(filter->GetFalseNegativeError(), 0.25, 1e-15);
EXPECT_NEAR(filter->GetFalsePositiveError(), 2.38418806475e-07, 1e-17);
EXPECT_NEAR(filter->GetFalseDiscoveryRate(), 0.25, 1e-15);
EXPECT_NEAR(filter->GetTargetOverlap(1), 0.5, 0.0);
EXPECT_NEAR(filter->GetUnionOverlap(1), 0.5, 0.0);
EXPECT_NEAR(filter->GetMeanOverlap(1), 2.0 / 3.0, 1e-15);
EXPECT_NEAR(filter->GetDiceCoefficient(1), 2.0 / 3.0, 1e-15);
EXPECT_NEAR(filter->GetVolumeSimilarity(1), -2.0 / 3.0, 1e-15);
EXPECT_NEAR(filter->GetFalseNegativeError(1), 0.5, 0.0);
EXPECT_NEAR(filter->GetFalsePositiveError(1), 0, 0.0);
EXPECT_NEAR(filter->GetFalseDiscoveryRate(1), 0, 0.0);
EXPECT_NEAR(filter->GetTargetOverlap(2), 1.0, 0.0);
EXPECT_NEAR(filter->GetUnionOverlap(2), 2.0 / 3.0, 2e-15);
EXPECT_NEAR(filter->GetMeanOverlap(2), 4.0 / 5.0, 1e-15);
EXPECT_NEAR(filter->GetDiceCoefficient(2), 4.0 / 5.0, 1e-15);
EXPECT_NEAR(filter->GetVolumeSimilarity(2), 2.0 / 5.0, 1e-15);
EXPECT_NEAR(filter->GetFalseNegativeError(2), 0.0, 0.0);
EXPECT_NEAR(filter->GetFalsePositiveError(2), 4.76837612950e-07, 1e-17);
EXPECT_NEAR(filter->GetFalseDiscoveryRate(2), 1.0 / 3.0, 0.0);
}
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