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GPU-accelerated computed laminography with application to non-destructive testing

: Maisl, Michael; Marsalek, Lukas; Horacek, Jan; Schorr, Christian; Slusallek, Philipp

Volltext urn:nbn:de:0011-n-3134070 (608 KByte PDF)
MD5 Fingerprint: 3fd8bffa73dc6a5602fced5de5af1b72
Erstellt am: 12.11.2014

Prevorovsky, Zdenek ; European Federation for Non-Destructive Testing -EFNDT-:
11th European Conference on Nondestructive Testing, ECNDT 2014. CD-ROM : October 6-10, 2014, Prague, Czech Republic; Conference proceedings
Brno: Brno University of Technology, 2014
ISBN: 978-80-214-5018-9
Beitrag 329
European Conference on Nondestructive Testing (ECNDT) <11, 2014, Prague>
Deutsche Forschungsgemeinschaft DFG
MA 5836/1-1
Parallel Iterative Methods with A Priori Information for Robust Computed Laminography of Low Contrast, Difficult-to-Measure-Objects
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IZFP ()
computed laminography; CLARA; GPU acceleration; iterative reconstruction methods

Computed tomography (CT) is a very powerful tool in medicine and non-destructive testing but it is unsuitable for planar objects like printed circuit boards or fiber reinforced plastics sheets, due to their strongly varying penetration lengths and spatial restrictions during the scan. A solution can be found in the use of computed laminography (CL), a technique where the object is irradiated by an oblique angle, thereby circumventing the problems arising in CT. The innovative scanner system CLARA (Computed laminography and radioscopy device) realizes this geometry in a new and efficient way, compared to existing industrial systems. Instead of four translational axes, CLARA only needs one rotational axis, greatly reducing both the costs and the calibration errors. Due to the limited amount of angular coverage and the specific geometric setup, filtered back projection methods used in CT cannot be employed for the reconstruction of laminographic projections. More flexible iterative algorithms like SART (simultaneous algebraic reconstruction technique) provide an answer to this challenge and also allow to incorporate a priori knowledge about the object to increase the reconstruction quality. The drawback of these algorithms lies in their high computational demands, resulting in typical reconstruction times in the order of hours. For certain practical applications this may be too time-consuming and therefore an acceleration of the algorithms is necessary. Compared to desktop central processing units (CPUs), modern graphics processing units (GPUs) contain an order of magnitude more cores designed specifically for massive data parallel processing. By designing new algorithms to fully exploit the GPU architecture, reconstruction times can be reduced from hours on a CPU to mere minutes on the GPU, thus allowing the practical use of computed laminography in industrial settings. Areas of application include the inspection of printed circuit boards, fiber reinforced plastics parts of wind energy plants and cars, as well as the general testing of sheet-like objects. We explain the advantages of the CLARA scanner and demonstrate the feasibility of computed laminography by means of CLARA results of industrially relevant inspection challenges using GPU-enhanced algorithms.