High-level algorithm prototyping: An example extending the TVR-DART algorithm

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Abstract

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.

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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 (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10502 LNCS, pp. 109–121). Springer Verlag. https://doi.org/10.1007/978-3-319-66272-5_10

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