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High-level algorithm prototyping: An example extending the TVR-DART algorithm
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
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2017 (English)In: Discrete Geometry for Computer Imagery: 20th IAPR International Conference, DGCI 2017, Vienna, Austria, September 19 – 21, 2017, Proceedings, Springer, 2017, p. 109-121Chapter in book (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer, 2017. p. 109-121
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743 ; 10502
National Category
Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-216705DOI: 10.1007/978-3-319-66272-5_10Scopus ID: 2-s2.0-85029482765ISBN: 9783319662718 OAI: oai:DiVA.org:kth-216705DiVA, id: diva2:1153358
Conference
19 September 2017 through 21 September 2017
Note

QC 20171030

Available from: 2017-10-30 Created: 2017-10-30 Last updated: 2017-10-30Bibliographically approved

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Ringh, AxelÖktem, Ozan
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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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  • nn-NO
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  • Other locale
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Output format
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