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WIP: ENH: Add watershed with distance map example.
Add watershed with distance map example. Resolves #48.
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‎src/Segmentation/Watersheds/CMakeLists.txt

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add_example(SegmentWithWatershedAndDistanceMap)
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compare_to_baseline(EXAMPLE_NAME SegmentWithWatershedAndDistanceMap
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TEST_NAME SegmentWithWatershedAndDistanceMapTest01BaselineComparison
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BASELINE_PREFIX SegmentWithWatershedAndDistanceMapTest01Baseline
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DEPENDS SegmentWithWatershedAndDistanceMapTest01
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TEST_IMAGE SegmentWithWatershedAndDistanceMapTest01.png
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)
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add_example(SegmentWithWatershedImageFilter)
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foreach( i RANGE 1 5 )

‎src/Segmentation/Watersheds/SegmentWithWatershedAndDistanceMap/BubbleVolume.csv.sha512

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0d5403fda7b3c94d3229bf5e42b523a4a5bb2cd84a45973011520daf5b3001192e74ff3d290b43c0feb0ebd84c17a328f4646a7887408c1f63e52927676f2360

‎src/Segmentation/Watersheds/SegmentWithWatershedAndDistanceMap/CMakeLists.txt

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cmake_minimum_required(VERSION 3.10.2)
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project(SegmentWithWatershedAndDistanceMap)
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find_package(ITK REQUIRED)
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include(${ITK_USE_FILE})
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add_executable(SegmentWithWatershedAndDistanceMap Code.cxx)
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target_link_libraries(SegmentWithWatershedAndDistanceMap ${ITK_LIBRARIES})
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install(TARGETS SegmentWithWatershedAndDistanceMap
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DESTINATION bin/ITKExamples/Segmentation/Watersheds
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COMPONENT Runtime
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)
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install(FILES Code.cxx CMakeLists.txt Code.py
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DESTINATION share/ITKExamples/Code/Segmentation/Watersheds/SegmentWithWatershedAndDistanceMap/
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COMPONENT Code
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)
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enable_testing()
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set(input_image ${CMAKE_CURRENT_BINARY_DIR}/PlateauBorder.tif)
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set(binarizingRadius01 2)
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set(majorityThreshold01 2)
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set(watershedThreshold01 0.01)
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set(watershedLevel01 0.5)
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set(cleaningStructuringElementRadius01 3)
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add_test(NAME SegmentWithWatershedAndDistanceMapTest01
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COMMAND ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/SegmentWithWatershedAndDistanceMap
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${input_image}
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ReversedInputImageTest01.tif
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DistanceMapImageTest01.tif
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WatershedImageTest01.tif
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SegmentWithWatershedAndDistanceMapTest01.tif
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${binarizingRadius01}
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${majorityThreshold01}
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${watershedThreshold01}
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${watershedLevel01}
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${cleaningStructuringElementRadius01}
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)
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if(ITK_WRAP_PYTHON)
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add_test(NAME SegmentWithWatershedAndDistanceMapTest01Python
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COMMAND ${PYTHON_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/Code.py
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${input_image}
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ReversedInputImageTest01.tif
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DistanceMapImageTest01.tif
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WatershedImageTest01.tif
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SegmentWithWatershedAndDistanceMapTest01Python.tif
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${binarizingRadius01}
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${majorityThreshold01}
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${watershedThreshold01}
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${watershedLevel01}
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${cleaningStructuringElementRadius01}
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)
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endif()

‎src/Segmentation/Watersheds/SegmentWithWatershedAndDistanceMap/Code.cxx

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/*=========================================================================
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*
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* Copyright NumFOCUS
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0.txt
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*
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*=========================================================================*/
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#include "itkBinaryBallStructuringElement.h"
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#include "itkBinaryMorphologicalOpeningImageFilter.h"
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#include "itkImageFileReader.h"
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#include "itkImageFileWriter.h"
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#include "itkScalarToRGBColormapImageFilter.h"
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#include "itkSignedMaurerDistanceMapImageFilter.h"
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#include "itkVotingBinaryIterativeHoleFillingImageFilter.h"
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#include "itkWatershedImageFilter.h"
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// Run with:
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// ./SegmentWithWatershedAndDistanceMap <inputImageFile>
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// <reversedInputImageFile> <distanceMapOutputImageFile>
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// <watershedOutputFileName> <segmentationResultOutputImageFile>
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// binarizingRadius majorityThreshold watershedThreshold watershedLevel
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// cleaningStructuringElementRadius
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// e.g.
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// ./SegmentWithWatershedAndDistanceMap PlateauBorder.tif
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// reversedInputImage.tif distanceMap.tif watershed.tif segmentationResult.tif
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// 2 2 0.01 0.5 3
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// (A rule of thumb is to set the threshold to be about 1 / 100 of the level.)
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int
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main(int argc, char * argv[])
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{
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if (argc < 10)
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{
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std::cerr << "Missing parameters." << std::endl;
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std::cerr << "Usage: " << argv[0] << " inputImageFile"
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<< " reversedInputImageFile"
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<< " distanceMapOutputImageFile"
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<< " watershedOutputFileName"
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<< " segmentationResultOutputImageFile"
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<< " binarizingRadius"
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<< " majorityThreshold"
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<< " watershedThreshold"
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<< " watershedLevel"
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<< " cleaningStructuringElementRadius" << std::endl;
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return EXIT_FAILURE;
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}
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constexpr unsigned int Dimension = 3;
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using UnsignedCharPixelType = unsigned char;
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using FloatPixelType = float;
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using InputImageType = itk::Image<UnsignedCharPixelType, Dimension>;
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using FloatImageType = itk::Image<FloatPixelType, Dimension>;
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using RGBPixelType = itk::RGBPixel<UnsignedCharPixelType>;
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using RGBImageType = itk::Image<RGBPixelType, Dimension>;
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using LabeledImageType = itk::Image<itk::IdentifierType, Dimension>;
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using FileReaderType = itk::ImageFileReader<InputImageType>;
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FileReaderType::Pointer reader = FileReaderType::New();
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reader->SetFileName(argv[1]);
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reader->Update();
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// Create bubble image: get a binarized version of the input image
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using VotingBinaryIterativeHoleFillingImageFilterType =
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itk::VotingBinaryIterativeHoleFillingImageFilter<InputImageType>;
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VotingBinaryIterativeHoleFillingImageFilterType::Pointer votingBinaryHoleFillingImageFilter =
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VotingBinaryIterativeHoleFillingImageFilterType::New();
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votingBinaryHoleFillingImageFilter->SetInput(reader->GetOutput());
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const unsigned int binarizingRadius = std::stoi(argv[6]);
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InputImageType::SizeType indexRadius;
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indexRadius.Fill(binarizingRadius);
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votingBinaryHoleFillingImageFilter->SetRadius(indexRadius);
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votingBinaryHoleFillingImageFilter->SetBackgroundValue(0);
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votingBinaryHoleFillingImageFilter->SetForegroundValue(255);
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const unsigned int majorityThreshold = std::stoi(argv[7]);
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votingBinaryHoleFillingImageFilter->SetMajorityThreshold(majorityThreshold);
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votingBinaryHoleFillingImageFilter->Update();
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using FileWriterType = itk::ImageFileWriter<InputImageType>;
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FileWriterType::Pointer reversedImageWriter = FileWriterType::New();
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reversedImageWriter->SetFileName(argv[2]);
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reversedImageWriter->SetInput(votingBinaryHoleFillingImageFilter->GetOutput());
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reversedImageWriter->Update();
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// Get the distance map of the input image
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using SignedMaurerDistanceMapImageFilterType =
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itk::SignedMaurerDistanceMapImageFilter<InputImageType, FloatImageType>;
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SignedMaurerDistanceMapImageFilterType::Pointer distanceMapImageFilter =
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SignedMaurerDistanceMapImageFilterType::New();
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distanceMapImageFilter->SetInput(votingBinaryHoleFillingImageFilter->GetOutput());
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distanceMapImageFilter->SetInsideIsPositive(false);
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distanceMapImageFilter->Update();
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using DistanceMapFileWriterType = itk::ImageFileWriter<FloatImageType>;
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DistanceMapFileWriterType::Pointer distanceMapWriter = DistanceMapFileWriterType::New();
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distanceMapWriter->SetFileName(argv[3]);
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distanceMapWriter->SetInput(distanceMapImageFilter->GetOutput());
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distanceMapWriter->Update();
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// Apply the watershed segmentation
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using WatershedFilterType = itk::WatershedImageFilter<FloatImageType>;
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WatershedFilterType::Pointer watershed = WatershedFilterType::New();
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const float watershedThreshold = std::stod(argv[8]);
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const float watershedLevel = std::stod(argv[9]);
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watershed->SetThreshold(watershedThreshold);
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watershed->SetLevel(watershedLevel);
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watershed->SetInput(distanceMapImageFilter->GetOutput());
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watershed->Update();
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using RGBFilterType = itk::ScalarToRGBColormapImageFilter<LabeledImageType, RGBImageType>;
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RGBFilterType::Pointer colormapImageFilter = RGBFilterType::New();
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colormapImageFilter->SetColormap(RGBFilterType::Jet);
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colormapImageFilter->SetInput(watershed->GetOutput());
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colormapImageFilter->Update();
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using WatershedFileWriterType = itk::ImageFileWriter<RGBImageType>;
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WatershedFileWriterType::Pointer watershedWriter = WatershedFileWriterType::New();
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watershedWriter->SetFileName(argv[4]);
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watershedWriter->SetInput(colormapImageFilter->GetOutput());
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watershedWriter->Update();
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// Clean the segmentation image: remove small objects by performing an
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// opening morphological operation
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using StructuringElementType =
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itk::BinaryBallStructuringElement<LabeledImageType::PixelType, LabeledImageType::ImageDimension>;
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StructuringElementType structuringElement;
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const unsigned int cleaningStructuringElementRadius = std::stoi(argv[10]);
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structuringElement.SetRadius(cleaningStructuringElementRadius);
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structuringElement.CreateStructuringElement();
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using BinaryMorphologicalOpeningImageFilterType =
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itk::BinaryMorphologicalOpeningImageFilter<LabeledImageType, LabeledImageType, StructuringElementType>;
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BinaryMorphologicalOpeningImageFilterType::Pointer openingFilter = BinaryMorphologicalOpeningImageFilterType::New();
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openingFilter->SetInput(watershed->GetOutput());
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openingFilter->SetKernel(structuringElement);
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openingFilter->Update();
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using SegmentationFileWriterType = itk::ImageFileWriter<RGBImageType>;
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SegmentationFileWriterType::Pointer segmentationWriter = SegmentationFileWriterType::New();
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segmentationWriter->SetFileName(argv[5]);
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segmentationWriter->SetInput(colormapImageFilter->GetOutput());
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segmentationWriter->Update();
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return EXIT_SUCCESS;
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}

‎src/Segmentation/Watersheds/SegmentWithWatershedAndDistanceMap/Code.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "9e8cfdc6",
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"metadata": {},
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"outputs": [],
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"source": [
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"import sys\n",
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"\n",
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"import itk\n",
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"import numpy as np\n",
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"\n",
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"from itkwidgets import view, cm\n",
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"import matplotlib.pyplot as plt"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "057c9f2f",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "962ea74edef74bc4b0b026a83f3dde3a",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Viewer(cmap=['bone_Matlab'], geometries=[], gradient_opacity=0.22, point_sets=[], rendered_image=<itk.itkImage…"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"stack_image = itk.imread('./PlateauBorder.tif')\n",
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"view(stack_image, cmap=[cm.bone])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"id": "ab956229",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "c0fc5e027fe149d4b4bc866b054c6e38",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Viewer(cmap=['bone_Matlab'], geometries=[], gradient_opacity=0.22, point_sets=[], rendered_image=<itk.itkImage…"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"binarizing_radius = 2\n",
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"majority_threshold = 2\n",
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"\n",
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"bubble_image = itk.voting_binary_hole_filling_image_filter(stack_image,\n",
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" radius=binarizing_radius,\n",
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" majority_threshold=majority_threshold,\n",
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" background_value=0,\n",
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" foreground_value=255)\n",
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"bubble_image = itk.invert_intensity_image_filter(bubble_image)\n",
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"view(bubble_image, cmap=[cm.bone,])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "bfc02551",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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