2015
DOI: 10.3233/fi-2015-1273
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Enhanced and Flexible Software Tools for X-ray Computed Tomography at the Italian Synchrotron Radiation Facility Elettra

Abstract: X-ray computed tomography (CT) experiments performed at synchrotron radiation facilities require adequate computing and storage resources due to the large amount of acquired and reconstructed data produced. To satisfy the heterogeneous needs of beamline users, flexible solutions are also required. Moreover, the growing demand of quantitative image analysis impose an easy integration between the CT reconstruction process and the subsequent feature extraction step. This paper presents some of the software soluti… Show more

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Cited by 103 publications
(67 citation statements)
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“…However, iterative approaches typically require more computational throughput (Sidky et al, 2006;Agulleiro & Fernandez, 2011;Treibig et al, 2013;Beister et al, 2012). Accelerators, such as GPUs, have been used to improve performance of iterative algorithms (Chilingaryan et al, 2010;Mirone et al, 2014;Brun et al, 2015;Vogelgesang et al, 2012), but memory limitations of these accelerators can introduce significant overheads due to the data movement from host to device memory. The TomoPy framework provides a complete set of tools for the portable analysis of tomography datasets, which can run on workstations (Gü rsoy et al, 2014).…”
Section: Related Workmentioning
confidence: 99%
“…However, iterative approaches typically require more computational throughput (Sidky et al, 2006;Agulleiro & Fernandez, 2011;Treibig et al, 2013;Beister et al, 2012). Accelerators, such as GPUs, have been used to improve performance of iterative algorithms (Chilingaryan et al, 2010;Mirone et al, 2014;Brun et al, 2015;Vogelgesang et al, 2012), but memory limitations of these accelerators can introduce significant overheads due to the data movement from host to device memory. The TomoPy framework provides a complete set of tools for the portable analysis of tomography datasets, which can run on workstations (Gü rsoy et al, 2014).…”
Section: Related Workmentioning
confidence: 99%
“…During this period of 24 min, the secondary liquid is moving and this needs to be taken into account when analysing the results. All the acquired data sets were phase-retrieved and then reconstructed using the custom developed software SYRMEP Tomo Project (Brun et al, 2015) using the filtered back projection reconstruction algorithm (Kak and Slaney, 1988). The optimized value for phase retrieval was set to 400.…”
Section: Image Analysismentioning
confidence: 99%
“…In this work, the same algorithm 345 was applied to synchrotron X-μCT data of garnets, acquired in phase-contrast mode, also with 346 polychromatic light (see Meyers et al 2007; Arzilli et al 2016). Phase-retrieval pre-processing was 347 carried out using the STP software (Brun et al 2015(Brun et al , 2017 employed also for tomographic 348 reconstruction. For the investigated garnet samples, a δ/β ratio equal to 100 was selected for phase-349 retrieval reconstructions (where δ is the refractive index decrement, proportional to the electron density 350 of a material, and β is called extinction coefficient, related to the absorption coefficient and 351 wavelength).…”
Section: Image Processing Of X-μct Data 326mentioning
confidence: 99%
“…The use of phase-contrast effects allows to detect very small details and to 265 highlight the interfaces between the different phases compared to the pure absorption mode. The 266 reconstruction of tomographic slices was carried out using the SYRMEP Tomo Project (STP) software 267 developed at Elettra (Brun et al 2015(Brun et al , 2017. 268…”
Section: Garnets and Their Anatectic Melt Inclusions 199mentioning
confidence: 99%