DocumentCode :
249523
Title :
On the Way to Big Data Applications in Industrial Computed Tomography
Author :
Ditter, Alexander ; Fey, D. ; Schon, Tobias ; Oeckl, Steven
Author_Institution :
Dept. of Comput. Sci., Univ. of Erlangen-Nuremberg, Erlangen, Germany
fYear :
2014
fDate :
June 27 2014-July 2 2014
Firstpage :
792
Lastpage :
793
Abstract :
Computed Tomography (CT) has been around, especially in the medical field, for more than 20 years. Although, the mathematical foundations for CT were known more than a century ago, technical limitations delayed its practical application for more than 70 years. Today, we can build CT systems large enough to scan an entire car, yet, for the processing of the resulting data we are facing a "Big (sensor) Data Problem". We currently do not have suitable methods and tools and cannot handle the large amount of data with conventional state-of-the-art techniques. As industrial CT became more and more prevalent over the last few years, especially due its unique features in the field of non destructive testing, we are proposing and evaluating the use of new methods, work flows and technologies, such as Cloud Computing, in order to provide suitable solutions for handling the steadily growing amount of data and its efficient processing.
Keywords :
cloud computing; computerised tomography; image reconstruction; nondestructive testing; 3D reconstruction; CT systems; acquisition time; big data applications; cloud computing; industrial CT; industrial computed tomography; medical field; nondestructive testing; scanned object; Big data; Computed tomography; Linear accelerators; Streaming media; Three-dimensional displays; Wide area networks; X-ray imaging; compression; industrial computed tomography; nondestructive testing; sensor data; streaming;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data (BigData Congress), 2014 IEEE International Congress on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4799-5056-0
Type :
conf
DOI :
10.1109/BigData.Congress.2014.125
Filename :
6906869
Link To Document :
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