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Speeding up image reconstruction in computed tomography

<!--HTML-->Computed tomography (CT) is a technique for imaging cross-sections of an object using X-ray measurements taken from different angles. In last decades a significant progress has happened there: today advanced algorithms allow fast image reconstruction and obtaining high-quality image...

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Autor principal: Tokareva, Victoria
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:http://cds.cern.ch/record/2307342
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author Tokareva, Victoria
author_facet Tokareva, Victoria
author_sort Tokareva, Victoria
collection CERN
description <!--HTML-->Computed tomography (CT) is a technique for imaging cross-sections of an object using X-ray measurements taken from different angles. In last decades a significant progress has happened there: today advanced algorithms allow fast image reconstruction and obtaining high-quality images even with missing or dirty data, modern detectors provide high resolution without increasing radiation dose, and high-performance multi-core computing devices are there to help us solving such tasks even faster. I will start with CT basics, then briefly present existing classes of reconstruction algorithms and their differences. After that I will proceed to employing distinctive architectural features of modern multi-core devices (CPUs and GPUs) and popular program interfaces (OpenMP, MPI, CUDA, OpenCL) for developing effective parallel realizations of image reconstruction algorithms. Decreasing full reconstruction time from long hours up to minutes or even seconds has a revolutionary impact in diagnostic medicine and industrial non-destructive testing applications.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2018
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spelling cern-23073422022-11-02T22:32:28Zhttp://cds.cern.ch/record/2307342engTokareva, VictoriaSpeeding up image reconstruction in computed tomographyInverted CERN School of Computing 2018Inverted CSC<!--HTML-->Computed tomography (CT) is a technique for imaging cross-sections of an object using X-ray measurements taken from different angles. In last decades a significant progress has happened there: today advanced algorithms allow fast image reconstruction and obtaining high-quality images even with missing or dirty data, modern detectors provide high resolution without increasing radiation dose, and high-performance multi-core computing devices are there to help us solving such tasks even faster. I will start with CT basics, then briefly present existing classes of reconstruction algorithms and their differences. After that I will proceed to employing distinctive architectural features of modern multi-core devices (CPUs and GPUs) and popular program interfaces (OpenMP, MPI, CUDA, OpenCL) for developing effective parallel realizations of image reconstruction algorithms. Decreasing full reconstruction time from long hours up to minutes or even seconds has a revolutionary impact in diagnostic medicine and industrial non-destructive testing applications.oai:cds.cern.ch:23073422018
spellingShingle Inverted CSC
Tokareva, Victoria
Speeding up image reconstruction in computed tomography
title Speeding up image reconstruction in computed tomography
title_full Speeding up image reconstruction in computed tomography
title_fullStr Speeding up image reconstruction in computed tomography
title_full_unstemmed Speeding up image reconstruction in computed tomography
title_short Speeding up image reconstruction in computed tomography
title_sort speeding up image reconstruction in computed tomography
topic Inverted CSC
url http://cds.cern.ch/record/2307342
work_keys_str_mv AT tokarevavictoria speedingupimagereconstructionincomputedtomography
AT tokarevavictoria invertedcernschoolofcomputing2018