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Investigation of Different Sparsity Transforms for the PICCS Algorithm in Small- Animal Respiratory Gated CT

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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.authorAbascal, Juan
dc.contributor.authorAbella García, Mónica
dc.contributor.authorSisniega, Alejandro
dc.contributor.authorVaquero López, Juan José
dc.contributor.authorDesco Menéndez, Manuel
dc.date.accessioned2015-04-07T12:54:14Z
dc.date.available2015-04-07T12:54:14Z
dc.date.issued2015-04-02
dc.descriptionData Availability Statement: All relevant data are available from the Zenodo database, under the DOI: http://dx.doi.org/10.5281/zenodo.15685.es
dc.description.abstractRespiratory gating helps to overcome the problem of breathing motion in cardiothoracic small-animal imaging by acquiring multiple images for each projection angle and then assigning projections to different phases. When this approach is used with a dose similar to that of a static acquisition, a low number of noisy projections are available for the reconstruction of each respiratory phase, thus leading to streak artifacts in the reconstructed images. This problem can be alleviated using a prior image constrained compressed sensing (PICCS) algorithm, which enables accurate reconstruction of highly undersampled data when a prior image is available. We compared variants of the PICCS algorithm with different transforms in the prior penalty function: gradient, unitary, and wavelet transform. In all cases the problem was solved using the Split Bregman approach, which is efficient for convex constrained optimization. The algorithms were evaluated using simulations generated from data previously acquired on a micro-CT scanner following a high-dose protocol (four times the dose of a standard static protocol). The resulting data were used to simulate scenarios with different dose levels and numbers of projections. All compressed sensing methods performed very similarly in terms of noise, spatiotemporal resolution, and streak reduction, and filtered back-projection was greatly improved. Nevertheless, the wavelet domain was found to be less prone to patchy cartoon-like artifacts than the commonly used gradient domain.es
dc.description.sponsorshipThis work was partially funded by the RICRETIC network (RD12/0042/0057) from the Ministerio de Economía y Competitividad (www.mineco.gob.es/) and projects TEC2010-21619-C04-01 and PI11/00616 from Ministerio de Ciencia e Innovación (www.micinn.es/). The research leading to these results was supported by funding from the Innovative Medicines Initiative (www.imi.europa.eu) Joint Undertaking under grant agreement n°115337, the resources of which comprise financial contributions from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies ("in kind contribution"). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.es
dc.format.extent18es
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationAbascal JFPJ, Abella M, Sisniega A, Vaquero JJ, Desco M (2015) Investigation of Different Sparsity Transforms for the PICCS Algorithm in Small-Animal Respiratory Gated CT. PLoS ONE 10 (4): e0120140.es
dc.identifier.doi10.1371/journal.pone.0120140
dc.identifier.publicationissue4es
dc.identifier.publicationtitlePLoS ONEes
dc.identifier.publicationvolume10es
dc.identifier.urihttps://hdl.handle.net/10016/20370
dc.language.isoenges
dc.relation.hasparthttp://dx.doi.org/10.5281/zenodo.15685
dc.relation.projectIDGobierno de España. RD12/0042/0057
dc.relation.projectIDGobierno de España. TEC2010-21619-C04-01
dc.relation.projectIDGobierno de España. PI11/00616
dc.relation.publisherversionhttp://dx.doi.org/10.1371/journal.pone.0120140es
dc.relation.uriinfo:eu-repo/semantics/dataset/doi/10.5281/zenodo.15685
dc.rights© The autorses
dc.rightsAtribución-NoComercial 3.0 España*
dc.rights.accessRightsopen accesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/es/*
dc.subject.ecienciaBiología y Biomedicinaes
dc.titleInvestigation of Different Sparsity Transforms for the PICCS Algorithm in Small- Animal Respiratory Gated CTes
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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