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First: fast iterative reconstruction software for (PET) tomography

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dc.affiliation.dptoUC3M. Departamento de Bioingenieríaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Biomedical Imaging and Instrumentation Groupes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: BSEL - Laboratorio de Ciencia e Ingeniería Biomédicaes
dc.contributor.authorHerraiz, J. L.
dc.contributor.authorEspaña, Samuel
dc.contributor.authorVaquero López, Juan José
dc.contributor.authorDesco Menéndez, Manuel
dc.contributor.authorUdías, José Manuel
dc.date.accessioned2011-08-03T07:35:55Z
dc.date.available2011-08-03T07:35:55Z
dc.date.issued2006
dc.description.abstractSmall animal PET scanners require high spatial resolution and good sensitivity. To reconstruct high-resolution images in 3D-PET, iterative methods, such as OSEM, are superior to analytical reconstruction algorithms, although their high computational cost is still a serious drawback. The higher performance of modern computers could make iterative image reconstruction fast enough to be viable, provided we are able to deal with the large number of probability coefficients for the system response matrix in high-resolution PET scanners, which is a difficult task that prevents the algorithms from reaching peak computing performance. Considering all possible axial and in-plane symmetries, as well as certain quasi-symmetries, we have been able to reduce the memory requirements to store the system response matrix (SRM) well below 1 GB, which allows us to keep the whole response matrix of the system inside RAM of ordinary industry-standard computers, so that the reconstruction algorithm can achieve near peak performance. The elements of the SRM are stored as cubic spline profiles and matched to voxel size during reconstruction. In this way, the advantages of ‘on-the-fly’ calculation and of fully stored SRM are combined. The on-the-fly part of the calculation (matching the profile functions to voxel size) of the SRM accounts for 10–30% of the reconstruction time, depending on the number of voxels chosen. We tested our approach with real data from a commercial small animal PET scanner. The results (image quality and reconstruction time) show that the proposed technique is a feasible solution
dc.description.sponsorshipPart of this work is funded by the IM3 network (Ministerio de Sanidad), with grants from the Ministerio de Educación y Ciencia, projects BFM2003-04147-C02-01 and TEC2004-07052-C02-01, Fondo de Investigaciones Sanitarias del Instituto de Salud Carlos III project PI052583 and Ministerio de Industria, Turismo y Comercio projects FIT-330101-2004-3 and CDTEAM (CENIT)
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationPhysics in Medicine and Biology, 2006, vol. 51, n. 18, p. 4547-4565
dc.identifier.doi10.1088/0031-9155/51/18/007
dc.identifier.issn0031-9155 (Print)
dc.identifier.issn1361-6560 (Online)
dc.identifier.publicationfirstpage4547
dc.identifier.publicationissue18
dc.identifier.publicationlastpage4565
dc.identifier.publicationtitlePhysics in Medicine and Biology
dc.identifier.publicationvolume51
dc.identifier.urihttps://hdl.handle.net/10016/11965
dc.language.isoeng
dc.publisherInstitute of Physics
dc.relation.publisherversionhttp://dx.doi.org/10.1088/0031-9155/51/18/007
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaBiología y Biomedicina
dc.titleFirst: fast iterative reconstruction software for (PET) tomography
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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