Difference between revisions of "ITK/Release 4 Planning"

From KitwarePublic
< ITK
Jump to navigationJump to search
Line 33: Line 33:
* Consolidate FEM Meshes and ITK Meshes
* Consolidate FEM Meshes and ITK Meshes


== Clean-up CMake Vars ==
== Backward compatibility and cleanup ==
* See proposal [[ITK_CMake_Style|HERE]].
* Clean-up CMake Vars ==
 
** See proposal [[ITK_CMake_Style|HERE]].
== Remove Deprecated Features ==
* Remove Deprecated Features
* Functions that have been deprecated (and appropriately marked as such) for more than 3 releases should be removed.
** Functions that have been deprecated (and appropriately marked as such) for more than 3 releases should be removed.
* 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++.
* 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 ==
== Image Registration ==
Line 50: Line 56:
* Modify transforms to support a consistent API across transform types
* Modify transforms to support a consistent API across transform types
* Modify order of parameters to be consistent across transforms.
* 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
== Composite Transform ==
* Define a composite transform which can contain any number of transforms, composed.
* Only expose the parameters of the last transform for optimization (default)
* Used in multivariate atlas formation (DTI reg with T1 reg with atlas)
* Remove all of the Centered transforms
* See Insight Journal Papers:
** http://www.insight-journal.org/browse/publication/143
** http://www.insight-journal.org/browse/publication/91


== Architecture ==
== Architecture ==
Line 78: Line 94:
** http://www.insight-journal.org/browse/publication/116
** http://www.insight-journal.org/browse/publication/116
** http://hdl.handle.net/1926/228
** http://hdl.handle.net/1926/228
== Composite Transform ==
* Define a composite transform which can contain any number of transforms, composed.
* Only expose the parameters of the last transform for optimization (default)
* Used in multivariate atlas formation (DTI reg with T1 reg with atlas)
* Remove all of the Centered transforms
* Modify the base class for optimizers to support key optimizer API calls such as SetMaximize and SetNumberOfIterations or SetMaximumIteration
* See Insight Journal Papers:
** http://www.insight-journal.org/browse/publication/143
** http://www.insight-journal.org/browse/publication/91


== Make as much filters as possible able to run in place ==
== Make as much filters as possible able to run in place ==
Line 100: Line 106:


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.
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.
== 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.


== Normalize the Binary/Label/Grayscale usage in code and in the class names ==
== Normalize the Binary/Label/Grayscale usage in code and in the class names ==
Line 111: Line 114:
== Testing framework ==  
== Testing framework ==  
Add a decent testing framework e.g. based on BOOST.test or googletest; see [http://www.itk.org/mailman/private/insight-developers/2008-December/011421.html discussion on the itk-developers]
Add a decent testing framework e.g. based on BOOST.test or googletest; see [http://www.itk.org/mailman/private/insight-developers/2008-December/011421.html discussion on the itk-developers]
== 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++.


== Code Revision Control ==
== Code Revision Control ==


* Migrate to Subversion
* Migrate to Subversion

Revision as of 16:23, 14 May 2009

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
  • 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

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.
  • 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++.
  • 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.
  • 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
  • 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

Composite Transform

Architecture

  • Implement a pure virtual base class for each API to support instantiation of templated filters at run-time with different dimensions.

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.

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

Testing framework

Add a decent testing framework e.g. based on BOOST.test or googletest; see discussion on the itk-developers

Code Revision Control

  • Migrate to Subversion