This directory contains a few basic notebooks to get you going. It is recommended to start with these before tackling any of the others.
object_oriented_programming is a notebook (independent of SIRF) that fits with a presentation given by Benjamin A. Thomas for CCP PETMR in 2017. Please watch the recording (note that screen sharing was enabled after about 4 minutes). You can also download the corresponding slides.
This notebook is not required for being able to use SIRF, but could help with understanding some of the concepts.
The introduction notebook serves as a starting point for all SIRF jupyter notebooks. The notebook shows how MR, PET and CT images can be created and manipulated.
The acquisition_model_mr_pet_ct notebook shows how to create a MR, PET and CT acquisition model and go from images to raw data and back again for each modality. (Do check notebooks for each modality for more information on the acquisition models.)
The gradient_descent_mr_pet_ct notebook shows how to write a simple gradient descent algorithm for MR, PET and CT (using CIL for the latter).
- Ensure you have a working version of SIRF (whether you're viewing this via a virtual machine, docker image, an Azure instance or a SIRF installation on your own machine). By the end of these notebooks, you should feel more comfortable with:
- Get a feel for Jupyter notebooks (and the basic python they require)
- Reading and displaying images
- Doing basic simulations and reconstruction in three different modalities
- Querying for help to improve knowledge of SIRF functionality.