Difference between revisions of "NAMIC Wiki:DTI:ITK"
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| − | + | This page host a discussion on the implementation details of a Tensor class. | |
| − | + | == Tensors and Traits == | |
| − | + | ||
| − | + | Torsten Rohlfing for SRI International Neuroscience Program proposed the following for ITK tensor processing: | |
| − | + | ||
| − | + | * Separate the operations which depend on the tensor size from those that do not. | |
| − | + | ** The former are in tensor traits, the latter are in tensor class. | |
| − | + | * Filter classes operate on different tensor pixel type images (by templating). | |
| − | + | ** The tensor classes can be more or less specialized. In particular, the filters will be able to support more general tensor classes that may be implemented later, as long as they provide the necessary interface functions for any given filter. | |
| − | + | * [[NAMIC_Wiki:DTI:ITK-SymmetricTensorPixelType:Header|itkSymmetricTensor.h]] | |
| − | + | ** Contains functions that do not benefit from knowledge of the tensor size, e.g., GetVnlMatrix() | |
| − | + | * [[NAMIC_Wiki:DTI:ITK-SymmetricTensorTraits::Header|itkSymmetricTensorTraits.h]] | |
| − | + | ** Operations that depend on the tensor size, e.g., eigenvalue computation. | |
| − | + | * itkTensorToFractionalAnisotropyImageFilter.{h,txx} | |
| − | + | ** Example filter that operates on tensor data. | |
| − | + | ** Operates on any tensor class that implements T::ComputeEigenvalues() | |
| − | + | * DiffusionTensorToFractionalAnisotropy.cxx | |
| − | + | ** Example application. Reads a tensor image from a raw data file, computes the FA image, and writes the result. | |
| − | + | ||
| − | + | === A First version of the SymmetricSecondRankTensor class committed to ITK === | |
| − | + | ||
| − | + | Given that Tensor can have any rank, from zero (scalar), one (vector), two (matrices) to N. It seemed appropriate to specify that this particular class was representing a symmetric tensor of second rank. | |
| − | + | ||
| − | + | The class has been committed into ITK (May 2 2005) and it is expected to evolve in the CVS repository. | |
| − | + | ||
| − | + | === A first version of SymmetricEigenAnalysis class committed to ITK === | |
| − | + | ||
| − | + | Serves as a thread safe alternative to vnl_symmetric_eigensystem, which calls netlib C routines is not thread safe. Please use this class in any multi-threaded filters. | |
| − | + | ||
| − | + | === A Hessian filter uses the Symmetric second rank tensor class === | |
| − | + | ||
| − | + | A filter for computing the Hessian of an image was also committed to ITK. This filter illustrates the first use of the SymmetricSecondRankTensor class as pixel type of an image. | |
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Latest revision as of 14:06, 18 December 2006
Home < NAMIC Wiki:DTI:ITKThis page host a discussion on the implementation details of a Tensor class.
Contents
Tensors and Traits
Torsten Rohlfing for SRI International Neuroscience Program proposed the following for ITK tensor processing:
- Separate the operations which depend on the tensor size from those that do not.
- The former are in tensor traits, the latter are in tensor class.
- Filter classes operate on different tensor pixel type images (by templating).
- The tensor classes can be more or less specialized. In particular, the filters will be able to support more general tensor classes that may be implemented later, as long as they provide the necessary interface functions for any given filter.
- itkSymmetricTensor.h
- Contains functions that do not benefit from knowledge of the tensor size, e.g., GetVnlMatrix()
- itkSymmetricTensorTraits.h
- Operations that depend on the tensor size, e.g., eigenvalue computation.
- itkTensorToFractionalAnisotropyImageFilter.{h,txx}
- Example filter that operates on tensor data.
- Operates on any tensor class that implements T::ComputeEigenvalues()
- DiffusionTensorToFractionalAnisotropy.cxx
- Example application. Reads a tensor image from a raw data file, computes the FA image, and writes the result.
A First version of the SymmetricSecondRankTensor class committed to ITK
Given that Tensor can have any rank, from zero (scalar), one (vector), two (matrices) to N. It seemed appropriate to specify that this particular class was representing a symmetric tensor of second rank.
The class has been committed into ITK (May 2 2005) and it is expected to evolve in the CVS repository.
A first version of SymmetricEigenAnalysis class committed to ITK
Serves as a thread safe alternative to vnl_symmetric_eigensystem, which calls netlib C routines is not thread safe. Please use this class in any multi-threaded filters.
A Hessian filter uses the Symmetric second rank tensor class
A filter for computing the Hessian of an image was also committed to ITK. This filter illustrates the first use of the SymmetricSecondRankTensor class as pixel type of an image.
