1. Getting Started with ITK in Python Language
I. Introduction to ITK, Python Wrapping and VTK-ITK Connection

2. Outline
ITK Overview (most slides are adopted from Documents in Insight Toolkit 1.2 CD)
Python Wrapping
Installations
Examples
Filter
Registration
ITK-VTK connection
Where to get help?

3. Open Source C++ Toolkit
What is ITK
Open Source C++ Toolkit
Medical Image
Processing
Registration
Segmentation

4. ITK Overview Core design concepts
Generic programming (e.g. temper late, containers, iterators.)
Smart pointers for memory management
Object factories for adaptable object instantiation
Command/observer design paradigm for event management
Multithreading support
Cross-platform (CMake)
Efficient n-dimensional implementation

5. The Big Picture
Common
Basic Filters
ITK
Numerics
Algorithms

6. Common Common System Data Pipeline Basic MultiThreader Mutex
Exceptions
Data
Basic
PointSet
Pipeline
Image
VectorContainer
MapContainer
ListFeatures
Histogram
Mesh
Point
Matrix
Vector
ProcessObject
DataObject
Events
Observer
Size
Transforms
Index

7. Numerics Numerics Optimizers VNL Statistics FEM Eigen SVD Matrix
Membership
Functions
Classifiers
Vector
Linear
Algebra
Evolutionary
Algorithms
Gradient
Descent
Histogram
methods
Optimizers
List
methods
Optimizers
VNL
Element
Statistics
Node
Numerics
Solver
FEM
Load
Material

8. Basic Filters Basic Filters PixelWise Neighborhood IO Global
Arithmetic
Basic Filters
PixelWise
Trigonometric
Intensity Transf
MorphoMath
Neighborhood IO
Median
Global
Derivative
Laplacian
EdgeDetection
PNG
VTK
DICOM
Meta
DistanceMap
HaussdorfDistance
Anisotropic
Diffusion
Connected
Components

9. Algorithms Algorithms Markov RF Level Sets Registration PDE
Interpolators
Narrow
Band
Shape
Detection
Fast
Marching
Transforms
Optimizers
Geodesic
Contours
Metrics
Multi
Resolution
Watershed
Markov RF
Level Sets
Registration
Demons
CurvatureFlow
PDE
Algorithms
Fuzzy
Connectedness
Hard
SimpleFuzzy
Deformable
Models
Balloon Force

10. Pipeline Architecture
Data Flow
Data Objects
Image
Mesh
Process Objects (Algorithms)
Segmentation
Registration
Image Processing
Streaming capable

11. Pipeline Architecture
Image
Filter

12. Streaming – Processing Large Images
Architecture
Streaming – Processing Large Images
Input
Image
Output
Image
Filter

13. Registration Framework
Multi Resolution Registration Framework
Image Registration Framework
Components
PDE Based Registration
FEM Based Registration

14. Registration Components
Registration Method
Fixed Image
Metric
Optimizer
Transform
Interpolator
Moving Image
Metric: Mutual Information, Mean Squares, Normalized Correlation and Pattern Intensity
Optimizer: Gradient Descent, Regular Step Gradient Descent, Conjugate Gradient, Levenberg-Marquardt
Transform: Translation, Scale, Rotation, Rigid3D, Rigid2D, Affine and Splines (TPS, EBS, VS)
Interpolator: Nearest neighbor, Linear, BSpline

15. Other Frameworks Level Set Framework for segmentation FEM Framework
A subsystem for solving general FEM problems, in particular non-rigid registration
IO Framework
Use a flexible object factory mechanism to support a variety of file formats

16. Why Python Wrapping ? Interpreted Language Interactive
Simplifies teaching and learning
Facilitates rapid prototyping
Large python-vtk user base in our Labs

17. How Does It Work? ITK Core is implemented in C++
Tcl and Python bindings are generated automatically using a combination of
gccxml -- a modified version of gcc
Cable -- processes XML info from gccxml and generates input for CSWIG
CSWIG -- modified version of SWIG that produces Python (or Tcl ) binding
Under active development, no binary installation package yet.

18. Python wrapping requires fully specified C++ types
How does it work ?
Python wrapping requires fully specified C++ types
C++
Python
Image<T,N>
Image<ushort,2>
ImageUS2
Image<ushort,3>
ImageUS3
Image<float,2>
ImageF2
Image<float,3>
ImageF3

19. How does it work ? ITK Filters are Templated over Image Type
GaussianImageFilter< InputImage, OutputImage >
GaussianImageFilter< ImageU2 , ImageU2 >
GaussianImageFilter< ImageF2 , ImageF2 >
GaussianImageFilter< ImageU2 , ImageF2 >
GaussianImageFilter< ImageF2 , ImageU2 >
GaussianImageFilter< ImageF3 , ImageU3 >

20. How does it work? C++ Python
Python wrapper for filters should define type combinations
C++
Python
GaussianImageFilter<ImageUS2,ImageUS2>
GaussianFilterUS2US2
GaussianImageFilter<ImageF2,ImageF2>
GaussianFilterF2F2
GaussianImageFilter<ImageUS2,ImageF2>
GaussianFilterUS2F2
GaussianImageFilter<ImageF2,ImageUS2>
GaussianFilterF2US2
GaussianImageFilter<ImageF3,ImageUS3>
GaussianFilterF3US3

21. VTK-ITK Connection in Python
Implemented as an module ConnectVTKITK in InsightApplication repository
Connect the pipeline with Import and Export classed in VTK and ITK
VTK exporter  ITK importer
ITK exporter  VTK importer
Use ITK for image processing, registration, segmentation and VTK for visualization
Status: Under active development

22. Installation What do I need?
C++ Compiler -- gcc 2.95 to 3.3, Visual C )
CMake (1.67 or cvs checkout)
Python (2.1, 2.2, or 2.3)
VTK (4.2.2 or cvs checkout)
Insight (cvs checkout)
InsightApplications
Installation for Python-VTK-ITK is not straight forward right now, no binary distribution. A step by step instruction will be posted on Image Lab coders’ web page.

23. Step 1 Python and modules
Linux comes with python and tcl/tk
Windows: python 2.2, tcl/tk 8.3
Numpy (Numeric Python)
Scientific Python (Install NetCDF library first for NetCDF and MINC support)

24. Step 2 CMake
Download the latest (1.67) binary for your platform from

25. Step 3 Install VTK
Install VTK from source distribution . Turn on the following flags
VTK_USE_HYBRID
VTK_USE_PATENTED
VTK_WRAP_PYTHON
VTK_USE_ANSI_STDLIB

26. Step 4 Install Insight Get the source cvs Build with CMake
CSWIG_WRAP_PYTHON
USE_VTK

27. Step 5 Install InsightApplications
CVS checkout
CMake
CONNECT_VTK_ITK

28. Step 6 Environment Variables
Linux/Unix
PYTHONPATH
LD_LIBRARY_PATY
Windows
PATH

29. Examples
CurvatureAnisotropicDiffusionImageFilter.py

30. Examples
ImageRegistration3.py

31. Examples : VTK-ITK Connection
CannyEdgeDetectionImageFilterConnectVTKITK.py

32. Where to get help? www.itk.org Image Labs coders mailing lists:
ITK Software Guild : PDF document (Over 500 pages)
Doxygen generated manual pages
Insight-users Mailing Lists
Image Labs coders mailing lists: