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dc.contributor.authorZeng, Kai
dc.contributor.authorBai, Erwei
dc.contributor.authorWang, Ge
dc.date.accessioned2017-09-18T10:05:29Z
dc.date.available2017-09-18T10:05:29Z
dc.date.issued2007-07-04
dc.identifier.citationKai Zeng, Erwei Bai, and Ge Wang, “A Fast CT Reconstruction Scheme for a General Multi-Core PC,” International Journal of Biomedical Imaging, vol. 2007, Article ID 29160, 9 pages, 2007. doi:10.1155/2007/29160
dc.identifier.urihttp://hdl.handle.net/10919/79075
dc.description.abstractExpensive computational cost is a severe limitation in CT reconstruction for clinical applications that need real-time feedback. A primary example is bolus-chasing computed tomography (CT) angiography (BCA) that we have been developing for the past several years. To accelerate the reconstruction process using the filtered backprojection (FBP) method, specialized hardware or graphics cards can be used. However, specialized hardware is expensive and not flexible. The graphics processing unit (GPU) in a current graphic card can only reconstruct images in a reduced precision and is not easy to program. In this paper, an acceleration scheme is proposed based on a multi-core PC. In the proposed scheme, several techniques are integrated, including utilization of geometric symmetry, optimization of data structures, single-instruction multiple-data (SIMD) processing, multithreaded computation, and an Intel C++ compilier. Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. Our scheme achieves a speedup of about 40, which can be further improved by several folds using the latest quad-core processors.
dc.format.mimetypeapplication/pdf
dc.language.isoenen_US
dc.publisherHindawien_US
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleA Fast CT Reconstruction Scheme for a General Multi-Core PCen_US
dc.typeArticle - Refereed
dc.date.updated2017-09-18T10:05:29Z
dc.description.versionPeer Reviewed
dc.rights.holderCopyright © 2007 Kai Zeng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en
dc.contributor.departmentSchool of Biomedical Engineering and Sciencesen_US
dc.identifier.doihttps://doi.org/10.1155/2007/29160
dc.type.dcmitypeText


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Creative Commons Attribution 4.0 International
License: Creative Commons Attribution 4.0 International