Draft:Operator Discretization Library

From Wikipedia, the free encyclopedia
Jump to navigation Jump to search
Original author(s)Jonas Adler, Holger Kohr and Ozan Öktem
Developer(s)The ODL Development Team
Initial release10 February 2015; 4 years ago (2015-02-10)
Written inPython
Operating systemLinux, macOS, Microsoft Windows
TypeMathematical software
LicenseMozilla Public License 2.0

Operator Discretization Library (ODL) is an open source toolbox for inverse problems written in python.

The main goal of ODL is to facilitate the use of advanced mathematical tools for real-world problems, without having to implement all necessary parts from the bottom up. The focus of the toolbox is fast prototyping in inverse problems. Its main audience is mathematicians and applied scientists in imaging [1][2][3][4][5][6][7].


ODL was initially developed at KTH Royal Institute of Technology as part of a research project funded by Swedish Foundation for Strategic Research [8][9]. It is currently being developed at [10]


  1. ^ Matěj, Zdeněk; Mokso, Rajmund; Larsson, Krister; Hardion, Vincent; Spruce, Darren (2017). "The MAX IV imaging concept". Advanced structural and chemical imaging. 2 (1). doi:10.1186/s40679-016-0029-7.
  2. ^ Adler, Jonas; Öktem, Ozan (2017). "Solving ill-posed inverse problems using iterative deep neural networks". Inverse Problems. 33 (12). doi:10.1088/1361-6420/aa9581.
  3. ^ Ringh, Axel; Zhuge, Xiaodong; Palenstijn, Willem Jan; Batenburg, Kees Joost; Öktem, Ozan (2017). "High-Level Algorithm Prototyping: An Example Extending the TVR-DART Algorithm". In Kropatsch, Walter G.; Artner, Nicole M.; Janusch, Ines (eds.). Discrete Geometry for Computer Imagery. Springer, Cham. pp. 109–121. doi:10.1007/978-3-319-66272-5_10. ISBN 978-3-319-66272-5.
  4. ^ Chen, Chong; Öktem, Ozan (2018). "Indirect image registration with large diffeomorphic deformations". SIAM Journal on Imaging Sciences. 11 (1): 575–617. doi:10.1137/17M1134627.
  5. ^ Buurlage, Jan-Willem; Kohr, Holger; Palenstijn, Willem Jan; Batenburg, Kees Joost (2018). "Real-time quasi-3D tomographic reconstruction". Measurement Science and Technology. 29 (6). doi:10.1088/1361-6501/aab754.
  6. ^ Zickert, Gustav; Maretzke, Simon (2018). "Cryogenic electron tomography reconstructions from phaseless data". Inverse Problems. 34 (12). doi:10.1088/1361-6420/aade22.
  7. ^ Marlevi, David (2019). Non-invasive imaging for improved cardiovascular diagnostics (PhD). KTH Royal Institute of Technology.
  8. ^ "Lågkomplexitetsrekonstruktionsmetoder för medicin". Retrieved 20 September 2019.
  9. ^ "ODL Github repository". Retrieved 23 May 2019.
  10. ^ Adler, Jonas; Kohr, Holger; et al. (9 September 2018). "odlgroup/odl: ODL 0.7.0". doi:10.5281/zenodo.1442734. Retrieved 20 September 2019.

External links[edit]