ITK/Release 4 Planning: Difference between revisions

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= Wish List =
= ITK Version 4 =
This work is supported by ARRA funding from the NLM. The [http://visual.nlm.nih.gov/itk/itk2010/agenda.html kick-off meeting] for this project took place from June 28-July 2 2010 in Bethesda. A beta version of the software will be available by the end of March 2011. Bug fixes will continue to be contributed to the ITK version 3 code.
== Download ==
 
* [[ITK_Release_4/Download|Download]]
 
== Release Notes ==
 
* [[ITK_Release_4/Migration Plan/Release Notes|Release Notes]]
 
== LICENSE Change ==
 
Starting with ITKv4-Alpha-01, the ITK toolkit is distributed under the Apache 2.0 License.
 
More details here:
 
* [[ITK_Release_4/Licensing|Licensing]]
 
== Revision Control ==
 
* Adopt a modern revision control system
** Move from cvs to [http://git-scm.com git] for distributed source code management
** [[ITK/Git|ITK Git Instructions]]
 
== Code Review ==
 
* Adopt a code review system
** [http://review.source.kitware.com/p/ITK ITK Gerrit]
** Powered by [http://code.google.com/p/gerrit/ Gerrit Code Review]
 
== Modern C++ ==
 
* [[ITK_Release_4/Modern C++|Modern C++]]
 
* Take advantage of advances in C++
** Target popular compilers that are compatible with the C++98 and/or C++03 standard (http://en.wikipedia.org/wiki/C%2B%2B03#Language_standard). 
** Specifically remove support for Visual Studio prior to 7.1 (e.g., 6 and 7.0),  Borland version 5.5, Sun Studio compilers prior to 5.9, IRIX compilers, MWORKS compilers, cygwin 1.5 (newer versions may work, but are not being targeted), and gcc prior to 3.4
 
== Wrapping ==
 
* Improved ITK Wrapping at the class level (WrapITK)
** [[ITK_Release_4/Wrapping|Wrapping]]
** Particularly for Python 2.x, Python 3, Java and C#
 
== Simplify ==
 
* Addition of [[ITK_Release_4/SimpleITK|Simple ITK Layer]]
 
== Modularize ==
 
* Refactor for [[ITK_Release_4/Modularization|Modularity]]
** ITKCore, ITKRegistrationModule, and Optional Modules
 
== Testing Crowdsourcing ==
 
* [[ITK_Release_4/Testing_Crowdsourcing|Testing Crowdsourcing]]
 
== Improve Software Process ==
 
* Enhanced project management tools and software processes
 
=== Data Management ===
 
* Better management for [[ITK_Release_4/Testing Data|Testing Data]]
* Data Collection [[ITK_Release_4/Data Collection|MIDAS]]
 
=== Distributed Testing (cdash@home) ===
 
* Testing On Demand [[ITK_Release_4/Testing On Demand|cdash@home]]
 
=== Testing Framework ===
 
* [[ITK_Release_4/UnitTesting|New unit testing framework]] based on [http://code.google.com/p/googletest/ Google Test]
** Particularly to support module development, testing, and maintenance
 
=== Coding Style ===
 
* [[ITK_Release_4/Coding Style|Coding Style]]
 
== Revise ==
 
=== FEM ===
 
* [[Refactoring itk::FEM framework - V4]]
 
=== Level Sets ===
 
* [[Refactoring Level-Set framework - V4]]
 
=== DICOM ===


== Oriented Images ==
* Improved DICOM support
* Support ND image in N+1 dimension
** [[ITK_Release_4/DICOM|DICOM]]
** 2D image can have an origin specified in 3D, thus a series of 2D images is not always Z-aligned
** Including communications with PACS
** Support ND images in M dimensions where M > N.
** Support Streaming interface
* All images are oriented - remove concept of an un-oriented image
** Add filter to support Siemens MOSAIC images
* Check use of orientation throughout ITK
** Information Object Definition verification
* Support re-orientation of ND oriented images
** Using anything other than 3D images won't compile with itkOrientedImageFilter


** Spatial Objects
=== Image Registration Framework ===
** Meshes
* Suggestions
** [[ITK_Release_4.0_Orientation_by_Kent]]
** [[ITK_Release_4.0_Orientation_by_Torsten]]
** [[ITK_Release_4.0_Orientation_by_Michael]]
** [http://wiki.na-mic.org/Wiki/index.php/Complex_Image_Set Some notes on complex image acquisitions by Steve and Greg]


== Image Representation ==
* [[ITK_Release_4/Enhancing Image Registration Framework|Enhancing Image Registration Framework]]
* 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
** [http://www.boost.org/doc/libs/1_39_0/libs/gil/doc/index.html Boost gil] also offers a compelling alternative for memory management of images. Unfortunately it seems to be still focused on 2D
* See [http://hdl.handle.net/10380/3068 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 ==
=== Spatial Objects ===
* Complete statistics refactoring (see NAMIC sandbox)


== FEM Meshes ==
* [[ITK_Release_4/SpatialObjects | Spatial Object Refactoring project page]]
* Consolidate FEM Meshes and ITK Meshes


== Backward compatibility and cleanup ==
=== Global Code Review ===
* Clean-up CMake Vars ==
** See proposal [[ITK_CMake_Style|HERE]].
* 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
** See this [http://www.itk.org/Bug/view.php?id=2893 bug report]
* 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 ==
* [[ITK_Release_4/Global_Code_Review | Global Code Review]]
* 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 [http://elastix.isi.uu.nl/doxygen/a00010.html 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 [http://elastix.isi.uu.nl/doxygen/a00193.html elastix] for another example implementation.
* Optimizers should return the best visited value
** See [http://public.kitware.com/Bug/bug_view_page.php?bug_id=3205 Bug 3205]
* 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.
** Currently several itk filters/functions assume that the pixel is of scalar type. This prevents from using the registration framework with vector images.
** Several filters/functions useful for registration are specialized for vectors whereas it is often unnecessary. It is often quite easy to adapt the filters that assume scalar pixels to make them work with vector pixels. For example, there is a [http://www.itk.org/Doxygen/html/classitk_1_1VectorInterpolateImageFunction.html VectorInterpolateImageFunction], but the regular [http://www.itk.org/Doxygen/html/classitk_1_1InterpolateImageFunction.html InterpolateImageFunction] should do just fine. Actually, there is even a [http://www.itk.org/cgi-bin/viewcvs.cgi/Testing/Code/Common/itkLinearInterpolateImageFunctionTest.cxx?root=Insight&sortby=date&view=markup unit test] to check that the [http://www.itk.org/Doxygen/html/classitk_1_1LinearInterpolateImageFunction.html LinearInterpolateImageFunction] correctly handles vector images. Below is a list of filters that could potentially be removed:
*** [http://www.itk.org/Doxygen/html/classitk_1_1VectorCastImageFilter.html VectorCastImageFilter]: could be reworked if we provide a conversion operator in the vector pixel class
*** [http://www.itk.org/Doxygen/html/classitk_1_1VectorCentralDifferenceImageFunction.html VectorCentralDifferenceImageFunction]
*** [http://www.itk.org/Doxygen/html/classitk_1_1VectorExpandImageFilter.html VectorExpandImageFilter]
*** [http://www.itk.org/Doxygen/html/classitk_1_1VectorImageNeighborhoodAccessorFunctor.html VectorImageNeighborhoodAccessorFunctor]
*** [http://www.itk.org/Doxygen/html/classitk_1_1VectorInterpolateImageFunction.html VectorInterpolateImageFunction]
*** [http://www.itk.org/Doxygen/html/classitk_1_1VectorResampleImageFilter.html VectorResampleImageFilter]
*** [http://www.itk.org/Doxygen/html/classitk_1_1VectorRescaleIntensityImageFilter.html VectorRescaleIntensityImageFilter]
*** [http://www.itk.org/Doxygen/html/classitk_1_1VectorRescaleIntensityImageFilter.html VectorRescaleIntensityImageFilter]
*** [http://www.itk.org/Doxygen/html/classitk_1_1VectorNeighborhoodInnerProduct.html VectorNeighborhoodInnerProduct]
*** [http://www.itk.org/Doxygen/html/classitk_1_1VectorNearestNeighborInterpolateImageFunction.html VectorNearestNeighborInterpolateImageFunction]
*** etc.
** In cases where the implementation has to be slightly different for vector pixels, we should consider using partial template specialization.
***This would require dropping support for visual c++ 6.
** An initial simple implementation of vector image registration can be found on the [http://www.na-mic.org/svn/NAMICSandBox/trunk/VectorImageRegistrationMethod/ NAMIC SandBox].


== Composite Transform ==
== Accelerate ==
* 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 and Software engineering ==
=== GPU ===
* 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. 
* [[ITK_Release_4/GPU Acceleration|GPU Acceleration - V4]]
** 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.
** With support for distributed computing in the future
** 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.


* Allow partial template specialization, (which would imply [[Proposals:Dropping_Support_for_Visual_Studio_6.0 |dropping support for VC 6.0]]).
* [[GPU_Acceleration_-_V4|GPU Acceleration - V4 (deprecated link)]]


* Discuss whether to move to TR1. Portability might be achieved through the [http://www.boost.org/doc/libs/1_39_0/doc/html/boost_tr1.html boost TR1 wrapper library].


* SmartPointer< T > should be implicitly convertible to SmartPointer< U > whenever T* can be implicitly converted to U*.
=== Numerical Libraries ===
** 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 [http://www.itk.org/cgi-bin/viewcvs.cgi/Testing/Code/Common/itkFactoryTestLib.cxx?root=Insight&view=markup itkFactoryTestLib.cxx] and [http://www.itk.org/cgi-bin/viewcvs.cgi/Testing/Code/Common/itkObjectFactoryTest2.cxx?root=Insight&view=markup itkObjectFactoryTest2].


* Testing framework
* [[ITK_Release_4/Refactor Numerical Libraries|Refactor Numerical Libraries]]
** 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]


* Code Revision Control
== Release schedules ==
** Migrate to Subversion


* Portability issues
* [[ITK Release 4/ReleaseSchedules|Release Schedules]]
** Discuss the use of fixed-width types to enhance portability and interoperability. This can be done by using [http://www.boost.org/doc/libs/1_39_0/boost/cstdint.hpp cstdint from boost].


== Internationalization ==
= The Team =
* Allow the use of unicode file names, see this [http://public.kitware.com/Bug/view.php?id=9623 bug report]


== Proper resampling/consistency in IndexToPhysicalPoint, ContinuousIndexToPhysicalPoint, Point* ==
[[ITK_Release_4/The Team|The Team]]
* Refactor all the interpolators
** See [[Proposals:Refactoring Index Point Coordinate System]]
** See [http://www.itk.org/Bug/view.php?id=6558 ITK Bug 6558]
** Fix bug 0005335 - transform initializer computes geometric center incorrectly


== Deformable Organisms ==
= Wish List =


* Move the framework from the IJ paper:
[[ITK_Release_4/Wish List|Wish List]]
** http://www.insight-journal.org/browse/publication/116
** http://hdl.handle.net/1926/228


== Make as much filters as possible able to run in place ==
= Migration Plan (Developers) =
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 ==
[[ITK_Release_4/Migration Plan|Migration Plan]]
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 ==
= Migration Guide (for Users) =


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.
[[ITK_Release_4/Users Migration Guide|Users Migration Guide]]


== Normalize the Binary/Label/Grayscale usage in code and in the class names ==
= Software Guide (Update) =
[[Proposals:Consistent_usage_of_label_and_binary_images]]


== Use an image template parameter in the complex related filters ==
[[ITK_Release_4/Software Guide Update|Software Guide Update]]


== Arbitrary precision type ==
= A2D2 Projects =


for reconstruction and geometry processing, you might want to use arbitrary precision type. Boost has one, GMP is now LGPL.
[[ITK_Release_4/A2D2_Projects|A2D2 Projects]]
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
= New Fields =


== Exact geometrical test (point in circle => delaunay ==
ITKv4 will provide improved support for


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.
* [[ITK_Release_4/Video|Video]]
* [[ITK_Release_4/Microscopy|Microscopy]]
* [[ITK_Release_4/Remote Sensing|Remote Sensing]]


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


== 3rd Party Libraries ==
[[ITK_Release_4/Discussion Points|Discussion Points]]


* Out dated libraries
= Outreach =
** 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
** The current linear algebra package used by ITK is VNL. It's performance and robustness is not very good, it is not actively maintained and cannot use a vendor back-end such as MKL. We should therefore discuss the alternative possibilities. Below is a list of potential linear algebra libraries:
** Boost [http://www.boost.org/doc/libs/release/libs/numeric uBLAS] with [http://mathema.tician.de/node/391 bindings] for LAPACK
*** [https://svn.boost.org/svn/boost/sandbox/numeric_bindings/ Trunk version of the automatically generated boost bindings]
*** [http://mathema.tician.de/software/boost-bindings Packaged version of the old hand-written version of boost bindings]
** [http://www.mcs.anl.gov/petsc/petsc-as/ PETSc]
** [http://home.gna.org/getfem/gmm_intro.html GMM++]
** [http://www.cs.uiowa.edu/~dstewart/meschach/ Meschach]
** [http://www.osl.iu.edu/research/mtl/ MTL] or [http://www.osl.iu.edu/research/mtl/mtl4/ MTL4]
** [http://eigen.tuxfamily.org Eigen] seems nice. It has quite a few linear algebra operations embedded and seems [http://eigen.tuxfamily.org/index.php?title=Benchmark very fast].
** 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].
* 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 [http://elastix.isi.uu.nl/doxygen/a00448.html elastix].


[[ITK_Release_4/Outreach|Outreach]]


== Coding Style ==
= New Code Contribution Process =


* 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.
[[ITK_Release_4/New_Code_Contribution_Process|New Code Contribution Process]]

Latest revision as of 15:59, 20 January 2012

ITK Version 4

This work is supported by ARRA funding from the NLM. The kick-off meeting for this project took place from June 28-July 2 2010 in Bethesda. A beta version of the software will be available by the end of March 2011. Bug fixes will continue to be contributed to the ITK version 3 code.

Download

Release Notes

LICENSE Change

Starting with ITKv4-Alpha-01, the ITK toolkit is distributed under the Apache 2.0 License.

More details here:

Revision Control

  • Adopt a modern revision control system

Code Review

Modern C++

  • Take advantage of advances in C++
    • Target popular compilers that are compatible with the C++98 and/or C++03 standard (http://en.wikipedia.org/wiki/C%2B%2B03#Language_standard).
    • Specifically remove support for Visual Studio prior to 7.1 (e.g., 6 and 7.0), Borland version 5.5, Sun Studio compilers prior to 5.9, IRIX compilers, MWORKS compilers, cygwin 1.5 (newer versions may work, but are not being targeted), and gcc prior to 3.4

Wrapping

  • Improved ITK Wrapping at the class level (WrapITK)
    • Wrapping
    • Particularly for Python 2.x, Python 3, Java and C#

Simplify

Modularize

  • Refactor for Modularity
    • ITKCore, ITKRegistrationModule, and Optional Modules

Testing Crowdsourcing

Improve Software Process

  • Enhanced project management tools and software processes

Data Management

Distributed Testing (cdash@home)

Testing Framework

Coding Style

Revise

FEM

Level Sets

DICOM

  • Improved DICOM support
    • DICOM
    • Including communications with PACS
    • Support Streaming interface
    • Add filter to support Siemens MOSAIC images
    • Information Object Definition verification

Image Registration Framework

Spatial Objects

Global Code Review

Accelerate

GPU


Numerical Libraries

Release schedules

The Team

The Team

Wish List

Wish List

Migration Plan (Developers)

Migration Plan

Migration Guide (for Users)

Users Migration Guide

Software Guide (Update)

Software Guide Update

A2D2 Projects

A2D2 Projects

New Fields

ITKv4 will provide improved support for

Discussion Points

Discussion Points

Outreach

Outreach

New Code Contribution Process

New Code Contribution Process