This is the repository for the X-ray tomography part of the course HL2027 in January 2018.

If you have any questions, please do not send me an e-mail, but open an issue in this repository, since you will certainly not be the only one with the same question.

Lecture slides can be found in the Lectures directory.

The exercise sheet can be found in the Exercise directory.

You will find a fully configured Python environment with GPUs and all libraries pre-installed under the address

http://radon.math.kth.se:8000

Please write an e-mail to banert snabel-a kth.se (my e-mail address at KTH) with the name of your github account to get access. Python is accessed via Jupyter notebooks (similar to e.g. Mathematica notebooks) in a very intuitive way. After the lab sessions, please download the notebooks to your personal computers, since access will be terminated shortly after the lab sessions.

You can also use your personal laptops for the lab session. Please install the master branch of ODL using the instructions on

https://github.com/adler-j/odlworkshop/blob/master/code/part0_install.ipynb
https://odlgroup.github.io/odl/getting_started/installing_source.html

(preferably using a conda environment; you will not need Tensorflow). Note that I cannot guarantee to be able to resolve potential problems for this variant.

• Timothy G. Feeman. The mathematics of medical imaging: A beginner’s guide. 2nd edition. Springer Undergraduate Texts in Mathematics and Technology. Springer, 2015. https://doi.org/10.1007/978-3-319-22665-1
• Jonas Adler and Holger Kohr. ODL course material. https://github.com/adler-j/odlworkshop
• Operator Discretization Library. https://github.com/odlgroup/odl
• Operator Discretization Library Documentation. https://odlgroup.github.io/odl/index.html