TomoBank: a tomographic data repository for computational x-ray science

• Published in: Measurement science & technology 2018-02, Vol.29 (3), p.34004
• Main Authors: De Carlo, Francesco, Gürsoy, Do a, Ching, Daniel J, Batenburg, K Joost, Ludwig, Wolfgang, Mancini, Lucia, Marone, Federica, Mokso, Rajmund, Pelt, Daniël M, Sijbers, Jan, Rivers, Mark
• Format: Article
• Language: English
• Subjects: Annan fysik; Fysik; KNOWLEDGE MANAGEMENT AND PRESERVATION; MATHEMATICS AND COMPUTING; Natural Sciences; Naturvetenskap; Other Physics Topics; Physical Sciences; tomographic data analysis; tomographic data archive; tomography; x-ray tomography
• ISSN: 0957-0233; 1361-6501
• DOI: 10.1088/1361-6501/aa9c19

There is a widening gap between the fast advancement of computational methods for tomographic reconstruction and their successful implementation in production software at various synchrotron facilities. This is due in part to the lack of readily available instrument datasets and phantoms representative of real materials for validation and comparison of new numerical methods. Recent advancements in detector technology have made sub-second and multi-energy tomographic data collection possible (Gibbs et al 2015 Sci. Rep. 5 11824), but have also increased the demand to develop new reconstruction methods able to handle in situ (Pelt and Batenburg 2013 IEEE Trans. Image Process. 22 5238-51) and dynamic systems (Mohan et al 2015 IEEE Trans. Comput. Imaging 1 96-111) that can be quickly incorporated in beamline production software (Gürsoy et al 2014 J. Synchrotron Radiat. 21 1188-93). The x-ray tomography data bank, tomoBank, provides a repository of experimental and simulated datasets with the aim to foster collaboration among computational scientists, beamline scientists, and experimentalists and to accelerate the development and implementation of tomographic reconstruction methods for synchrotron facility production software by providing easy access to challenging datasets and their descriptors.