ITK/Release 4 Planning: Difference between revisions

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** Unify with the underlying routines of Numpy/Scipy [http://www.scipy.org]
** Unify with the underlying routines of Numpy/Scipy [http://www.scipy.org]
*** Some uBLAS/numpy bindings are available from [http://mathema.tician.de/software/pyublas pyUlas].
*** Some uBLAS/numpy bindings are available from [http://mathema.tician.de/software/pyublas pyUlas].
* A fairly complete list of potential libraries can be found at [http://verdandi.gforge.inria.fr/doc/linear_algebra_libraries.pdf]
* Numerical analysis package
* Numerical analysis package
** The current numerical analysis package used by ITK is VNL. It's performance and robustness is not very good, it is not actively maintained. We should therefore discuss the alternative possibilities. Below is a list of potential alternatives:
** The current numerical analysis package used by ITK is VNL. It's performance and robustness is not very good, it is not actively maintained. We should therefore discuss the alternative possibilities. Below is a list of potential alternatives:
** The main numerical analysis tools we use from vnl are the optimizers. Most of these optimizers have an alternative quasi-ITK implementation in [http://elastix.isi.uu.nl/doxygen/a00448.html elastix].
** The main numerical analysis tools we use from vnl are the optimizers. Most of these optimizers have an alternative quasi-ITK implementation in [http://elastix.isi.uu.nl/doxygen/a00448.html elastix].


== Coding Style ==
== Coding Style ==


* The current descriptive naming scheme is certainly good to get a grip on the functionality, but the length of the names are, IMHO getting a bit out of hand. I would suggest to group similar classes into namespaces, like e.g. MeanSquaresImageToImageMetric and MatchCardinalityImageToImageMetric, and the likes into ImageToImageMetric and use the specific part as new class name (MeanSquares, MatchCardinality).  For those preferring the long version ImageToImageMetric::MeanSquares is at least as descriptive, and others could use the using directive in their code. These namespaces would also help with the automatically generated documentation since classes would be better grouped by having namespace related pages instead of only the flat alphabetical ordering that currently exists. For backward compatibility, one could provide defines that should, of course, be only enabled as deprecated feature.
* The current descriptive naming scheme is certainly good to get a grip on the functionality, but the length of the names are, IMHO getting a bit out of hand. I would suggest to group similar classes into namespaces, like e.g. MeanSquaresImageToImageMetric and MatchCardinalityImageToImageMetric, and the likes into ImageToImageMetric and use the specific part as new class name (MeanSquares, MatchCardinality).  For those preferring the long version ImageToImageMetric::MeanSquares is at least as descriptive, and others could use the using directive in their code. These namespaces would also help with the automatically generated documentation since classes would be better grouped by having namespace related pages instead of only the flat alphabetical ordering that currently exists. For backward compatibility, one could provide defines that should, of course, be only enabled as deprecated feature.

Revision as of 07:43, 4 February 2010

Wish List

Oriented Images

  • Support ND image in N+1 dimension
    • 2D image can have an origin specified in 3D, thus a series of 2D images is not always Z-aligned
    • Support ND images in M dimensions where M > N.
  • All images are oriented - remove concept of an un-oriented image
  • Check use of orientation throughout ITK
  • Support re-orientation of ND oriented images
    • Using anything other than 3D images won't compile with itkOrientedImageFilter

Image Representation

  • Allow the use of strides that are not equal to the image width
    • Would ease the collaboration of ITK with opencv
    • Would allow the use of sse operations
    • Might be considered redundant with correct use of image regions but is not since GetLargestPossibleRegion should correspond to the image width and not its stride
  • Drop the itk::Image::GetBufferPointer() method
    • This method has been many time described as a problem to implement new image layouts.
    • As expressed above, we need however to be able to use the memory held by ITK images within other libraries. This could potentially be done by making itk::Image be only a base class that has no knowledge of the memory layout and by implementing different image subclasses.
  • Consider replacing ImportImageContainer by std::vector or using std::vector to implement it
    • This would give STL iterators that operate on the whole image literally for free and make it easy to use a lot of algorithms implemented in STL and BOOST
    • Boost gil also offers a compelling alternative for memory management of images. Unfortunately it seems to be still focused on 2D
  • See Alternative Memory Models for ITK Images on the Insight Journal for an initial implementation of such ideas
  • Discuss a proper way of handling dynamic images (2D+t is not really 3D and 3D+t is difficult in terms of memory management)

Statistics

  • Complete statistics refactoring (see NAMIC sandbox)

FEM Meshes

  • Consolidate FEM Meshes and ITK Meshes

Backward compatibility and cleanup

  • Clean-up CMake Vars ==
  • Remove Deprecated Features
    • Functions that have been deprecated (and appropriately marked as such) for more than 3 releases should be removed.
  • Modify the itkSetMacro to use a const reference argument, i.e. #define itkSetMacro(name,type) virtual void Set##name (const type & _arg)
    • This cannot be done int ITK 3.x because of backward compatibility issues
  • Make the semantics of the ITK containers match th one from STL
  • Set the default options values to provide the highest result quality
    • Some filters have default options values to produce quick transforms rather than high quality transforms. This is the case for the distance map filters, which produced squared results and don't use image spacing by default. This behavior is desirable in some conditions, but shouldn't be the default one.
  • Supported compilers
    • We should reconsider the list of supported compilers. ITK 4.0 might be a good time to drop, for example, MSVC 6.0 that only implements a subset of modern C++.
    • I would even suggest to go so far as to pick a very small set of very recent compilers that already implement support for parts of the new, upcoming C++0x standard. As an alternative one could also keep changes on the list of supported compilers a little bit more open until this standard is released and fully supported by a wider range of compilers.
  • Define a transition period during which developments need not be backward compatible
    • Such a period could be defined in terms of a number of "beta" releases

Image Registration

  • Set up the infrastructure to ease the implementation of modern optimization schemes for image registration
    • Requires Hessian or pseudo-Hessians of the cost function
    • Requires several types of update rules (additive, compositional, inverse compositional, etc.)
    • References: "Lucas-Kanade 20 years on" by Baker et al.; "Homography-based 2D Visual Tracking and Servoing" by Benhimane and Malis, "Groupwise Geometric and Photometric Direct Image Registration" by Bartoli; etc.
  • Allow the use of regularization terms that depends on the spatial transformation. See elastix for an example implementation.
  • Clean up the use of parameter scaling in the optimizers
    • One possibility would be that the optimizers only perform unscaled minimization. It would then be up to a cost function wrapper to do the rescaling and potentially return the opposite of the cost function. This is similar to how vnl optimizers are used in ITK
    • See also elastix for another example implementation.
  • Optimizers should return the best visited value
  • Modify transforms to support a consistent API across transform types
  • Modify order of parameters to be consistent across transforms.
  • Modify the base class for optimizers to support key optimizer API calls such as SetMaximize and SetNumberOfIterations or SetMaximumIteration
  • Make the registration framework work with vector images natively.

Composite Transform

Architecture and Software engineering

  • Implement a pure virtual base class for each API to support instantiation of templated filters at run-time with different dimensions. Many classes in ITK are templated, for example over spatial dimension and pixel type, or over images that are templated over spatial dimension and pixel type. However, many of the operations that are carried out do not depend on the spatial dimension and pixel type. A pure virtual base class for a particular filter, such as itk::ResampleImageFilter, would define the API of the ResampleImageFilter without implementing any of the functions that depend on TInputImage, TOutputImage or TInterpolatorPrecisionType. This would enable a pointer to the virtual base class to be manipulated in code,

and a specialized implementation with a particular TInputImage, TOutputImage and TInterpolatePrecisionType to be instantiated at run time. This would enable an image to be read in, its dimension and pixel type to be established at run time, an appropriate specialized class to be instantiated and used, rather than the current practice of fixing at compile time the dimension and pixel type that will be utilized. For example, a single program could be written using the virtual base class API with run-time instantiation of a 2D filter for floating point pixels if the input is a 2D with floating point pixels, and a 3D filter with unsigned short pixels if the input is 3D with unsigned short pixels.

Can you explain a bit more?

  • Add interfaces to the algorithms that turn incomplete initialization into compile time error for "linear" environments or enable some kind of validation instead of throwing an exception in "dynamic" environments. In both cases, the entry points to doing real work of the algorithm should then be guarded by assertions regarding the required parameters, not exceptions - since ending up there without proper initialization would always be a programming error.
    • As a "linear" environments I define an implementations where the parameters and the input to an algorithm are completely determined by the program. In this case, an error in initialization (by missing a SetXXX method) usually is a programming error. Adding an initialization method or constructor that takes all required parameters would enable the developer to move this error from run-time to compile-time.
    • As a "dynamic" environments I imagine e.g. a GUI program, where the user can set the parameters to an algorithm dynamically. Here, a missing SetXXX is not a programming error, but a user error. However, since more than one parameter might be missing, exceptions are not a good way to report the problem. Instead, it should be possible to call some validation function that reports all the missing parameters to the user.
  • SmartPointer< T > should be implicitly convertible to SmartPointer< U > whenever T* can be implicitly converted to U*.
    • This might be achieved by using TR1 smart pointers instead of the ITK 3.0 smart pointer implementation. It might however then be more complex to use the default factory mechanism as with itkFactoryTestLib.cxx and itkObjectFactoryTest2.
  • Code Revision Control
    • Migrate to Subversion
  • Portability issues
    • Discuss the use of fixed-width types to enhance portability and interoperability. This can be done by using cstdint from boost.
    • Avoid the use of tryrun in the cmakelist and rely only on trycompile to ease cross-compilation

Internationalization

  • Allow the use of unicode file names, see this bug report

Proper resampling/consistency in IndexToPhysicalPoint, ContinuousIndexToPhysicalPoint, Point*

Deformable Organisms

Make as much filters as possible able to run in place

In place computation is a great way to avoid running out of memory when updating a pipeline. We should review all the existing filters to find the filters which could be implemented that way, and use InPlaceImageFilter has their base class. Also, a global setting to control the default in place/not in place behavior would be great.

Make the boundary conditions usage consistent across the toolkit

At the moment, some filters let the user provide a boundary condition, some don't but use one internally, and some just don't use them at all. This should be consistent in the toolkit, and if it make sense, it should be changeable by the user. Boundary conditions also make some filters hard to enhance with much more efficient algorithms - see BoxMeanImageFilter for an example.

Replace the current implementation of Marching Cubes and add a 4D version

The itkBinaryMask3DMeshSource filter currently provides the closest functionality to the Marching Cubes algorithm in ITK. However the code of this filter has to be rewritten in order to match the quality standards of the rest of the toolkit. As part of this rewrite we should provide implementations for 2D (marching squares), 3D marching cubes and a 4D version that could be used for segmenting 3D+time datasets.

Normalize the Binary/Label/Grayscale usage in code and in the class names

Proposals:Consistent_usage_of_label_and_binary_images

Use an image template parameter in the complex related filters

Arbitrary precision type

for reconstruction and geometry processing, you might want to use arbitrary precision type. Boost has one, GMP is now LGPL. That also could be a feature of the numerical library, and then the solvers could directly use this, if needed.

inspired from exct and filtered kernels in CGAL

Exact geometrical test (point in circle => delaunay

If we cannot go for arbitrary precision types, in some case it is sufficient to support some operations to have exact geometrical predicates. This is mandatory for a robust delaunay implementation. The implementation for the point-in-circle predicate which is necessary and sufficient for exact 2D delaunay, is public domain.

Note that abitrary precision would allow for any exact geometrical predicates.

3rd Party Libraries

  • Out dated libraries
    • Many 3rd party libraries (ex libTIFF) are years out of date. One possibility is to update them to their newest official release. Another is to remove them and require developers to use their own version (i.e. USE_SYSTEM_TIFF).
  • Linear algebra package
  • A fairly complete list of potential libraries can be found at [2]
  • Numerical analysis package
    • The current numerical analysis package used by ITK is VNL. It's performance and robustness is not very good, it is not actively maintained. We should therefore discuss the alternative possibilities. Below is a list of potential alternatives:
    • The main numerical analysis tools we use from vnl are the optimizers. Most of these optimizers have an alternative quasi-ITK implementation in elastix.

Coding Style

  • The current descriptive naming scheme is certainly good to get a grip on the functionality, but the length of the names are, IMHO getting a bit out of hand. I would suggest to group similar classes into namespaces, like e.g. MeanSquaresImageToImageMetric and MatchCardinalityImageToImageMetric, and the likes into ImageToImageMetric and use the specific part as new class name (MeanSquares, MatchCardinality). For those preferring the long version ImageToImageMetric::MeanSquares is at least as descriptive, and others could use the using directive in their code. These namespaces would also help with the automatically generated documentation since classes would be better grouped by having namespace related pages instead of only the flat alphabetical ordering that currently exists. For backward compatibility, one could provide defines that should, of course, be only enabled as deprecated feature.
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