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dboundboun
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Move code from CaPTk
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‎CMake/BuildConfigurations/InteractiveSegmentationConfiguration.cmake

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### Inspired by https://github.com/MIC-DKFZ/MITK-Diffusion/blob/master/CMake/BuildConfigurations/DiffusionAll.cmake
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### Basically when selected, the following will turn on automatically
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message(STATUS "Configuring Interactive Segmentation default optional dependencies")
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# Enable non-optional external dependencies
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set(MITK_USE_OpenCV ON CACHE BOOL "" FORCE)
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# Enable/disable non-superbuild apps
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set(MITK_BUILD_APP_Workbench ON CACHE BOOL "Build the MITK Workbench executable" FORCE)
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# Enable/disable non-superbuild plugins
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set(MITK_BUILD_org.mitk.gui.qt.segmentation ON CACHE BOOL "Build the org.mitk.gui.qt.segmentation Plugin." FORCE)
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set(MITK_BUILD_org.mitk.gui.qt.multilabelsegmentation ON CACHE BOOL "Build the org.mitk.gui.qt.multilabelsegmentation Plugin." FORCE)
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# Activate in-application help generation
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set(MITK_DOXYGEN_GENERATE_QCH_FILES ON CACHE BOOL "Use doxygen to generate Qt compressed help files for MITK docs" FORCE)
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set(BLUEBERRY_USE_QT_HELP ON CACHE BOOL "Enable support for integrating bundle documentation into Qt Help" FORCE)
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# Disable console window
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set(MITK_SHOW_CONSOLE_WINDOW OFF CACHE BOOL "Use this to enable or disable the console window when starting MITK GUI Applications" FORCE)
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# Enable exporting of compile commands (useful for intellisense in vscode etc)
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set(CMAKE_EXPORT_COMPILE_COMMANDS ON CACHE BOOL "Enable/Disable output of compile commands during generation." FORCE)

‎CMake/Findyaml-cpp.cmake

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# Nothing here

‎CMake/PackageDepends/MITK_yaml-cpp_Config.cmake

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list(APPEND ALL_LIBRARIES ${YAML_CPP_LIBRARIES})
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if(YAML_CPP_INCLUDE_DIR)
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list(APPEND ALL_INCLUDE_DIRECTORIES ${YAML_CPP_INCLUDE_DIR})
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endif()

‎CMakeExternals/ExternalProjectList.cmake

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mitkFunctionAddExternalProject(NAME yaml-cpp ON DOC "Use YAML Cpp Library")

‎CMakeExternals/yaml-cpp.cmake

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set(proj yaml-cpp)
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set(proj_DEPENDENCIES "")
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if(MITK_USE_${proj})
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set(${proj}_DEPENDS ${proj})
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if(DEFINED ${proj}_DIR AND NOT EXISTS ${${proj}_DIR})
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message(FATAL_ERROR "${proj}_DIR variable is defined but corresponds to non-existing directory!")
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endif()
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if(NOT DEFINED ${proj}_DIR)
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ExternalProject_Add(${proj}
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GIT_REPOSITORY https://github.com/jbeder/yaml-cpp.git
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GIT_TAG yaml-cpp-0.6.3
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CMAKE_ARGS ${ep_common_args}
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CMAKE_CACHE_ARGS ${ep_common_cache_args}
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-DGSL_CXX_STANDARD:STRING=${MITK_CXX_STANDARD}
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-DGSL_TEST:BOOL=OFF
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-DYAML_BUILD_SHARED_LIBS:BOOL=ON
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-DYAML_CPP_BUILD_TESTS:BOOL=OFF
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CMAKE_CACHE_DEFAULT_ARGS ${ep_common_cache_default_args}
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DEPENDS ${proj_DEPENDENCIES}
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)
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set(${proj}_DIR ${ep_prefix})
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else()
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mitkMacroEmptyExternalProject(${proj} "${proj_DEPENDENCIES}")
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endif()
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endif()

‎LICENSE

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By installing the Cancer and Phenomics Toolkit (CaPTk), the user agrees to the following licenses, which pertain to the code and its different constituents:
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1. SBIA Software License - https://www.med.upenn.edu/sbia/software-agreement.html
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2. SBIA Non-Commercial Software License (applies to PHI Estimator) - https://www.med.upenn.edu/sbia/software-agreement-non-commercial.html
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3. Insight Toolkit License - https://cmake.org/Wiki/ITK/License_Information
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4. Visualization Toolkit License - http://www.vtk.org/licensing/
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5. Qt Open Source License - https://doc.qt.io/qt-5.10/qtcore-index.html#licenses-and-attributions; our copy can be found at https://github.com/CBICA/qt
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6. CC Attribution-ShareAlike for SRI24 data - https://creativecommons.org/licenses/by-sa/3.0/us/legalcode
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7. MRIcroGL License - BSD
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8. YAML-CPP - MIT License and can be found at https://opensource.org/licenses/MIT
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9. Eigen - MPL2 License and can be found at https://www.mozilla.org/en-US/MPL/2.0/
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10. MITK - BSD-style license http://www.mitk.org/wiki/License

‎Modules/CaPTkInteractiveSegmentation/CMakeLists.txt

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mitk_create_module(
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INCLUDE_DIRS PUBLIC include third_party/jsoncpp/include
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PACKAGE_DEPENDS ITK Qt5|Core+Widgets PRIVATE yaml-cpp
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DEPENDS PUBLIC MitkCore MitkMultilabel #MitkCaPTkCommon
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)
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add_subdirectory(cmdapps)

‎Modules/CaPTkInteractiveSegmentation/README.md

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## CaPTkInteractiveSegmentation
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Contains the algorithm part of the interactive segmentation.
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It uses brief, user-drawn seeds on co-registered input images to produce a segmentation.
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For UI look at the respective plugin.

‎Modules/CaPTkInteractiveSegmentation/cmdapps/CMakeLists.txt

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option(BUILD_CaPTkInteractiveSegmentationCmdApp "Build command-line app for CaPTkInteractiveSegmentation" OFF)
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if(BUILD_CaPTkInteractiveSegmentationCmdApp)
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mitkFunctionCreateCommandLineApp(
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NAME CaPTkInteractiveSegmentation
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CPP_FILES "${SRC_FILES}" CaPTkInteractiveSegmentation.cpp
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PACKAGE_DEPENDS ITK OpenCV Qt5|Core+WebEngineWidgets
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DEPENDS MitkCaPTkInteractiveSegmentation
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)
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endif()

‎Modules/CaPTkInteractiveSegmentation/cmdapps/CaPTkInteractiveSegmentation.cpp

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#include <mitkCommandLineParser.h>
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#include <mitkIOUtil.h>
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#include <mitkDataStorage.h>
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#include <mitkStandaloneDataStorage.h>
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#include <mitkImageCast.h>
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#include <CaPTkInteractiveSegmentation.h>
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#include <GeodesicTrainingSegmentation.h>
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// #include <json/json.h>
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#include <algorithm>
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#include <string>
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#include <fstream>
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#include <iostream>
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#include <memory>
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/**Splits a string into a list using a delimiter*/
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std::vector<std::string>
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split(const std::string &s, char delim) {
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std::stringstream ss(s);
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std::string item;
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std::vector<std::string> elems;
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while (std::getline(ss, item, delim)) {
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elems.push_back(std::move(item));
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}
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return elems;
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}
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/** \brief command-line app for batch processing of images
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*
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* This command-line app takes a task and and a cohort and runs the algorithm on everything.
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*/
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int main(int argc, char* argv[])
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{
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mitkCommandLineParser parser;
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/**** Set general information about the command-line app ****/
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parser.setCategory("CaPTk Cmd App Category");
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parser.setTitle("CaPTk Interactive Segmentation Cmd App");
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parser.setContributor("CBICA");
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parser.setDescription(
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"This command-line app takes a task and cohort and runs the interactive segmentation algorithm on everything.");
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// How should arguments be prefixed
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parser.setArgumentPrefix("--", "-");
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/**** Add arguments. Unless specified otherwise, each argument is optional.
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See mitkCommandLineParser::addArgument() for more information. ****/
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parser.addArgument(
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"images",
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"i",
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mitkCommandLineParser::String,
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"Images",
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"Paths to the input images, separated by comma",
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us::Any(),
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false);
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parser.addArgument(
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"labels",
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"l",
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mitkCommandLineParser::String,
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"Labels Image",
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"Path to the input seeds image.",
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us::Any(),
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false);
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parser.addArgument(
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"priorimages",
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"p",
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mitkCommandLineParser::String,
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"Prior Images",
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"These are also input images, but are generated by a deep learning algorithm",
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us::Any(),
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true);
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parser.addArgument(
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"outputdir",
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"o",
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mitkCommandLineParser::String,
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"Output Directory",
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"Where to generate the output",
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us::Any(),
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false);
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// // Add arguments. Unless specified otherwise, each argument is optional.
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// // See mitkCommandLineParser::addArgument() for more information.
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// parser.addArgument(
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// "task",
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// "t",
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// mitkCommandLineParser::String,
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// "Task",
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// "JSON file that contains information on how to run this execution.",
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// us::Any(),
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// false);
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// parser.addArgument(
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// "cohort",
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// "c",
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// mitkCommandLineParser::String,
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// "Cohort",
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// "JSON file that contains information on how to run this execution.",
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// us::Any(),
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// false);
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/**** Parse arguments. This method returns a mapping of long argument names to
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their values. ****/
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auto parsedArgs = parser.parseArguments(argc, argv);
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if (parsedArgs.empty())
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return EXIT_FAILURE; // Just exit, usage information was already printed.
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if (parsedArgs["task"].Empty() || parsedArgs["cohort"].Empty())
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{
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MITK_INFO << parser.helpText();
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return EXIT_FAILURE;
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}
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// // Parse, cast and set required arguments
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// auto task = us::any_cast<std::string>(parsedArgs["task"]);
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// auto cohort = us::any_cast<std::string>(parsedArgs["cohort"]);
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auto imagesPaths = us::any_cast<std::string>(parsedArgs["images"]);
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auto labelsPath = us::any_cast<std::string>(parsedArgs["labels"]);
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auto outputDir = us::any_cast<std::string>(parsedArgs["outputdir"]);
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/**** Default values for optional arguments ****/
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std::string priorImagesPaths = "";
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// // Parse, cast and set optional arguments
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if (parsedArgs.end() != parsedArgs.find("priorimages"))
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{
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priorImagesPaths = us::any_cast<std::string>(parsedArgs["priorimages"]);
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}
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std::vector<std::string> imagesPathsVector = split(imagesPaths, ',');
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std::vector<std::string> priorImagesPathsVector = split(priorImagesPaths, ',');
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/**** Run ****/
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try
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{
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std::vector<mitk::Image::Pointer> images;
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std::vector<mitk::Image::Pointer> priorImages;
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mitk::LabelSetImage::Pointer seeds;
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/**** Read input ****/
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for (std::string& imagePath : imagesPathsVector)
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{
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auto image = mitk::IOUtil::Load<mitk::Image>(imagePath);
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images.push_back(image);
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}
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for (auto& priorImagePath : priorImagesPathsVector)
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{
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auto priorImage = mitk::IOUtil::Load<mitk::Image>(priorImagePath);
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priorImages.push_back(priorImage);
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}
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seeds = mitk::IOUtil::Load<mitk::LabelSetImage>(labelsPath);
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// auto algorithm = new CaPTkInteractiveSegmentation(nullptr);
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// algorithm->Run(task, cohort);
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if (images[0]->GetDimension() == 3)
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{
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// [ 3D ]
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/**** Convert to itk ****/
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std::vector<itk::Image<float,3>::Pointer> imagesItk;
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std::vector<itk::Image<float,3>::Pointer> priorImagesItk;
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typename itk::Image<int,3>::Pointer seedsItk;
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for (auto& image : images)
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{
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typename itk::Image<float, 3>::Pointer imageItk;
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mitk::CastToItkImage(image, imageItk);
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imagesItk.push_back(imageItk);
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}
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for (auto& image : priorImages)
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{
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typename itk::Image<float, 3>::Pointer imageItk;
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mitk::CastToItkImage(image, imageItk);
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priorImagesItk.push_back(imageItk);
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}
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mitk::CastToItkImage(seeds, seedsItk);
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std::unique_ptr<GeodesicTrainingSegmentation::Coordinator<float,3>> geodesicTraining(
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new GeodesicTrainingSegmentation::Coordinator<float,3>()
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);
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geodesicTraining->SetInputImages(imagesItk);
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geodesicTraining->SetExtraInputImagesNotAGDable(priorImagesItk);
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geodesicTraining->SetLabels(seedsItk);
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geodesicTraining->SetOutputPath(outputDir);
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// geodesicTraining->SetNumberOfThreads(16);
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// geodesicTraining->SaveOnlyNormalSegmentation(true, "segmentation");
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geodesicTraining->SetVerbose(true);
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/**** Run algorithm ****/
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auto result = geodesicTraining->Execute();
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if (result->ok)
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{
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mitk::Image::Pointer segmNormal;
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mitk::CastToMitkImage(result->labelsImage, segmNormal);
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mitk::LabelSetImage::Pointer segm = mitk::LabelSetImage::New();
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segm->InitializeByLabeledImage(segmNormal);
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mitk::IOUtil::Save(segm, outputDir + std::string("/segmentation.nii.gz"));
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}
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else {
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std::cout << "Algorithm finished with internal error\n";
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return EXIT_FAILURE;
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}
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}
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else
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{
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// [ 2D ]
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std::cout << "2D not supported yet\n";
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return EXIT_FAILURE;
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}
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return EXIT_SUCCESS;
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}
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catch (const std::exception &e)
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{
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MITK_ERROR << e.what();
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return EXIT_FAILURE;
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}
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catch (...)
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{
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MITK_ERROR << "Unexpected error!";
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return EXIT_FAILURE;
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}
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}

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