[ITK-users] Medical Image Analysis IPython Notebooks

[Bradley Lowekamp]

Hello Kevin,

These notebooks look outstanding. Thank you very much for sharing.

I very much like what you did here:
http://nbviewer.ipython.org/github/ozan-oktay/Medical-Image-Analysis-IPython-Tutorials/blob/master/tutorial_2/basics_reg.ipynb
to illustrate the different metrics' values, and the impact of apply Gaussian smoothing to the images.

Also please note that you were using the an experimental version of the ImageRegistrationMethod in SimpleITK which was based on ITKv3 registration frameworks. Since then the development has evolved to be based on the ITKv4 registration framework and many, many features have been added.

This includes a couple transform initializers which estimate some basic transform parameters and very importantly set the fixed parameter for the center of the transform. Additionally the interface to the transforms is much improved.

Brad

On Dec 20, 2014, at 5:24 AM, Kevin Keraudren <kevin.keraudren10 at imperial.ac.uk> wrote:

> Hi,
> 
> The IPython notebooks used for the tutorials in the Medical Image Analysis course at Imperial College London are now on github:
> https://github.com/ozan-oktay/Medical-Image-Analysis-IPython-Tutorials
> 
> These might be of interest to the mailing list as they rely on SimpleITK and could be useful either as teaching material or example applications.
> 
> They can be browsed directly in nbviewer:
> http://nbviewer.ipython.org/github/ozan-oktay/Medical-Image-Analysis-IPython-Tutorials/tree/master/
> 
> The following blog post is a quick presentation of the github repository:
> http://kevin-keraudren.blogspot.co.uk/2014/12/medical-image-analysis-ipython-tutorials.html
> 
> Please do not hesitate to let us  know if you have questions or comments regarding these tutorials.
> 
> Kind regards,
> 
> Kevin Keraudren,
> PhD student, Imperial College London
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