This repository provides colab python notebooks (you can also run these notebooks using jupyter) that help beginners to learn and practice image registration in a simple way using arrays. I try to explain the math behind image registration components using simple python code.
Your feedback and support is appreciated.
Contents:
- Image registration using mean square metric, 2d translation transform, and gradient descent
- TODO 03: implement a simple interpolation
- TODO 04: implement a simple transformation
- Image registration using mutual information, 2d translation transform, and gradient descent
- Image registration using mean square metric, 2d translation transform, and stochastic gradient descent
- Image registration using mutual information, 2d translation transform, and stochastic gradient descent
- Image registration using mean square metric, 2d rigid transform, and gradient descent
- Image registration using mutual information, 2d rigid transform, and gradient descent
- Image registration using mean square metric, 2d rigid transform, and stochastic gradient gradient descent
- Image registration using mutual information, 2d rigid transform, and stochastic gradient gradient descent
Other TODOs:
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Colab Tutorial:
- colab interface and menus
- create a notebook and run your first code
- navigate between sections.
- Advance:
- customise you keyboard shortcut
- change runtime type
- connect to google drive
- basic linux commands
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Youtube version with English and Arabic languages.
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Youtube: building ITK from source on clean ubuntu 20.04 system , building and run first example, tracing some code.