Difference between revisions of "AHM2013-Simple-ITK"

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Presenters: Bradley Lowekamp
 
Presenters: Bradley Lowekamp
  
SimpleITK is an abstraction layer on top of ITK which provides Python bindings for many of the algorithms in ITK. The tool is still under active development and recent additions have focus on providing a more Pythonic interface to Image class, numerous additional algorithms, and the addition of transforms and interpolators.
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SimpleITK is an abstraction layer on top of ITK which provides Python bindings for many of the algorithms in ITK. The tool is under active development and recent additions have focus on providing a more Pythonic interface to Image class, numerous additional algorithms, and the addition of transforms and interpolators.
  
SimpleITK is a build option in Slicer3D when using ITKv4
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SimpleITK is a build option in Slicer3D when using ITKv4. It can provide many powerful algorithms to Slicer as
  
 
Version 0.6.0rc01 is scheduled available for binary download on January 6th.
 
Version 0.6.0rc01 is scheduled available for binary download on January 6th.

Revision as of 21:13, 3 January 2013

Home < AHM2013-Simple-ITK

Presenters: Bradley Lowekamp

SimpleITK is an abstraction layer on top of ITK which provides Python bindings for many of the algorithms in ITK. The tool is under active development and recent additions have focus on providing a more Pythonic interface to Image class, numerous additional algorithms, and the addition of transforms and interpolators.

SimpleITK is a build option in Slicer3D when using ITKv4. It can provide many powerful algorithms to Slicer as

Version 0.6.0rc01 is scheduled available for binary download on January 6th.


This presentation will consist of a slide presentation covering the fundamental concepts and style of SimpleITK. Along with the numerous Python specific features available. Then interactive demonstration of SimpleITK with be done in the iPython notebook environment utilizing the pylab functionality to demonstrate algorithms in ITK along with Pythonic work flows.

Attendees are encouraged to setup a python environment to follow along in this session.

Under the best of circumstances (tested on OSX 10.8) this environment can be setup with the following:

sudo pip install virutalenv
virtualenv ~/sitkpy --no-site-packages
~/sitkpy/bin/pip install ipython
~/sitkpy/bin/pip install ipython[zmq]
~/sitkpy/bin/pip install Tornado
~/sitkpy/bin/pip install numpy
~/sitkpy/bin/pip install matplotlib
~/sitkpy/bin/easy_install SimpleITK

To launch:

~/sitkpy/bin/ipython notebook --pylab=inline

Note: On Linux platforms you may be able to obtain many of these packages as system packages which may suffice ( Ubuntu 12+). Note: On Window platforms some of these packages should be obtained as binary downloads and installed.