GPU-based fast iterative reconstruction of fully 3-D PET sinograms

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dc.contributor.author Herraiz, J. L.
dc.contributor.author España, Samuel
dc.contributor.author Cabido, R.
dc.contributor.author Montemayor, A. S.
dc.contributor.author Desco Menéndez, Manuel
dc.contributor.author Vaquero López, Juan José
dc.contributor.author Udías, José Manuel
dc.date.accessioned 2012-06-25T11:52:38Z
dc.date.available 2012-06-25T11:52:38Z
dc.date.issued 2011-10
dc.identifier.bibliographicCitation IEEE Transactions on Nuclear Science, vol. 58, n. 5, october 2011. Pp. 2257-2263
dc.identifier.issn 0018-9499
dc.identifier.uri http://hdl.handle.net/10016/14673
dc.description.abstract This work presents a graphics processing unit (GPU)- based implementation of a fully 3-D PET iterative reconstruction code, FIRST (Fast Iterative Reconstruction Software for [PET] Tomography), which was developed by our group. We describe the main steps followed to convert the FIRST code (which can run on several CPUs using the message passing interface [MPI] protocol) into a code where the main time-consuming parts of the reconstruction process (forward and backward projection) are massively parallelized on a GPU. Our objective was to obtain significant acceleration of the reconstruction without compromising the image quality or the flexibility of the CPU implementation. Therefore, we implemented a GPU version using an abstraction layer for the GPU, namely, CUDA C. The code reconstructs images from sinogram data, and with the same System Response Matrix obtained from Monte Carlo simulations than the CPU version. The use of memory was optimized to ensure good performance in the GPU. The code was adapted for the VrPET small-animal PET scanner. The CUDA version is more than 70 times faster than the original code running in a single core of a high-end CPU, with no loss of accuracy.
dc.description.sponsorship This work was supported in part by AMIT Project funded by CDTI (CENIT Programme), UCM (Grupos UCM, 910059), CPAN (Consolider-Ingenio 2010, CSPD-2007-00042), RECAVA- RETIC network, Comunidad de Madrid (ARTEMIS S2009/DPI-1802), Ministerio de Ciencia e Innovación, Spanish Government (ENTEPRASE grant, PSE-300000-2009-5 and TEC2007-64731/TCM), and European Regional funds.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher IEEE
dc.rights © IEEE
dc.subject.other CUDA
dc.subject.other Graphics processing units
dc.subject.other Image reconstruction
dc.subject.other Positron Emission Tomography (PET)
dc.title GPU-based fast iterative reconstruction of fully 3-D PET sinograms
dc.type article
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1109/TNS.2011.2158113
dc.subject.eciencia Biología y Biomedicina
dc.identifier.doi 10.1109/TNS.2011.2158113
dc.rights.accessRights openAccess
dc.relation.projectID Comunidad de Madrid. S2009/DPI-1802/ARTEMIS
dc.relation.projectID Gobierno de España. PSE-300000-2009-5
dc.relation.projectID Gobierno de España. TEC2007-64731/TCM
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 2257
dc.identifier.publicationissue 5
dc.identifier.publicationlastpage 2263
dc.identifier.publicationtitle IEEE Transactions on Nuclear Science
dc.identifier.publicationvolume 58
dc.identifier.uxxi AR/0000009408
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