Operator Discretization Library (ODL) is an open-source Python library for prototyping reconstruction methods for inverse problems, and ASTRA is a high-performance Matlab/Python toolbox for large-scale tomographic reconstruction. The paper demonstrates the feasibility of combining ODL with ASTRA to prototype complex reconstruction methods for discrete tomography. As a case in point, we consider the total-variation regularized discrete algebraic reconstruction technique (TVR-DART). TVR-DART assumes that the object to be imaged consists of a limited number of distinct materials. The ODL/ASTRA implementation of this algorithm makes use of standardized building blocks, that can be combined in a plug-and-play manner. Thus, this implementation of TVR-DART can easily be adapted to account for application specific aspects, such as various noise statistics that come with different imaging modalities.

Additional Metadata
Persistent URL dx.doi.org/10.1007/978-3-319-66272-5_10
Conference Discrete Geometry for Computer Imagery
Citation
Ringh, A, Zhuge, X, Palenstijn, W.J, Batenburg, K.J, & Öktem, O. (2017). High-level algorithm prototyping: An example extending the TVR-DART algorithm. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 109–121). doi:10.1007/978-3-319-66272-5_10