ITK/Release 4/Why Switch to ITKv4: Difference between revisions
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=== WrapITK === | === WrapITK === | ||
* Tight incorporation of the outstanding formerly third party [http://code.google.com/p/wrapitk WrapITK] project. | * Tight incorporation of the outstanding, formerly third party [http://code.google.com/p/wrapitk WrapITK] project. | ||
* [http://numpy.scipy.org Numpy] integration. | * [http://numpy.scipy.org Numpy] integration. |
Revision as of 21:59, 1 September 2011
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 the External module.
- Find the quality control per module by performing code coverage tests per module.
New Registration Framework
- Automatic optimization parameter scale estimation
- Composite transform
- Displacement field transform
- Better integration of dense displacement field registration into the framework
- Better support for multi-threading
- Additional evolutionary optimizers
- Different B-Spline registration approach available
- Transform symmetric second rank tensors
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 levels 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
- Ease of Use
- Rapid development
- Interactive processing