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Talk50 min

Speeding up image reconstruction in computed tomography

Victoria Tokareva · CERN

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About

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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The talk

  1. Speeding up image reconstruction in computed tomography 2018-03-06 · 50 min · CERN's player

Credits and licence

Institution
CERN
Department
Inverted CSC
Speaker
Victoria Tokareva
Year
2018
Language
English
Subjects
Computer science
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
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