ITK/Release 4/Why Switch to ITKv4
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Modularization
- Easier to find what you are looking for.
- Easier to understand how to use the toolkit.
- Build only the parts of the toolkit that you need.
- Extend bridging of the toolkit to other toolkit and libraries.
- Makes it easy to associate and build auxiliary community projects with an External module.
- Find the quality control per module by performing code coverage tests per module.
New Finite Element Registration Framework
- Better conformity with the rest of the toolkit
- Improved IO of objects and results
New Registration Framework
- New unified and fully multi-threaded optimization and registration framework
- Unified framework supports sparse and dense metric computation
- Unified framework supports low and high dimensional mapping
- Improved multi-threaded metrics for rigid, affine and deformable registration
- New metrics support sparse or dense sampling
- Metrics for landmark or label guided registration
- Automatic parameter scale estimation for registration
- Automatic step-size selection for gradient-based registration optimizers
- Composite transforms and composite transform optimization
- Displacement field and diffeomorphic velocity field-based transforms
- Better support for multi-threading in optimizers and metrics
- Additional evolutionary optimizers
- Improved B-Spline registration approach available and bug fixes to old framework
- Accurately transform and reorient covariant tensors and vectors
New LevelSets Segmentation Framework
- Powerful, modular architecture
- Now you, too, can fully understand how level sets are implemented!
- Easy to extend and customize
- Simultaneously evolve multiple level sets on an image
- Faster
- Limit evolution to a domain
- Three different sparse representations available, Whitaker, Shi, Malcolm
- Design avoids duplication of calculations in many ways
- Easy conversion from BinaryMask or LabelMap to a level set.
SimpleITK
- Easy to use
- Procedural Interface Examples:
- [[ http://www.itk.org/SimpleITKDoxygen/html/SimpleGaussianProcedural_8py-example.html | Procedual Gaussian in Python ]]
- [[ http://www.itk.org/SimpleITKDoxygen/html/SimpleGaussianFunctional_8cxx-example.html | Procedural Gaussian in C++]]
- Object Oriented Interface Examples:
- [[ http://www.itk.org/SimpleITKDoxygen/html/SimpleGaussian_8cxx-example.html | OOP Gaussian in C++ ]]
- [[ http://www.itk.org/SimpleITKDoxygen/html/SimpleGaussian_8py-example.html | OOP Gaussian in Python ]]
- [[ http://www.itk.org/SimpleITKDoxygen/html/SimpleGaussian_8java-example.html | OOP Gaussian in Java ]]
- [[ http://www.itk.org/SimpleITKDoxygen/html/SimpleGaussian_8cs-example.html | OOP Gaussian in C# ]]
- Additional Examples:
- Illustrations of ITK, WrappedITK, and SimpleITK
- Procedural Interface Examples:
- Rapid development
- Interactive processing
Software Process
- Fast, distributed, powerful version control: Git
- Better support for making contributions
- Low barrier to entry
- Well defined contribution process
- Use powerful tools, Git branches, Gerrit reviews
- Get code into the toolkit quicker
- Get higher quality code in with more reviews and platform testing
- Forget SETI@home, give the aliens a reason to visit by improving ITK with CDash@home!
- Know when/if your bug will be addressed with the scrum process in the JIRA issue tracker
- Flexible management of testing data
WrapITK
"You can do it!"
- Migration Guide
- ITKv4 Removed or renamed classes|
- The insight-users mailing list is there for you.
- Transition is easier with ITKV3_COMPATIBILITY configuration option.
- Many deprecated classes are still available.
- The list of other improvements and new features are legion, don't miss out!