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:

• 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

• Youtube version with English and Arabic languages.

• Youtube: building ITK from source on clean ubuntu 20.04 system , building and run first example, tracing some code.