This repository contains the code for the article "Learning to solve inverse problems using Wasserstein loss".
The code contains the following
- Training using circle phantoms
The pre-trained networks are currently under finalization and will be released soon, in the meantime, training is just a few hours.
The code is currently based on the latest version of ODL and the utility library adler. They can be most easily installed by running
$ pip install https://github.com/odlgroup/odl/archive/master.zip
$ pip install https://github.com/adler-j/adler/archive/master.zipThe learning requires tensorflow, and the ray-transform needs ASTRA for computational feasibility
$ conda install -c astra-toolbox astra-toolboxJonas Adler, PhD student
KTH, Royal Institute of Technology
Elekta
[email protected]
Axel Ringh, PhD student
KTH, Royal Institute of Technology
[email protected]
Ozan Öktem, Associate Professor
KTH, Royal Institute of Technology
[email protected]
Johan Karlsson, Associate Professor
KTH, Royal Institute of Technology
[email protected]
Development is financially supported by the Swedish Foundation for Strategic Research as part of the project "Low complexity image reconstruction in medical imaging" and "3D reconstruction with simulated forward models".
Development has also been financed by Elekta.