Real-time 3D PET image with pseudoinverse reconstruction

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Show simple item record López-Montes, Alejandro Galve, Pablo Udias Moinelo, José Manuel Cal-González, Jacobo Vaquero López, Juan José Desco Menéndez, Manuel Herraiz, Joaquín L. 2020-11-25T13:28:49Z 2020-11-25T13:28:49Z 2020-04-19
dc.identifier.bibliographicCitation Applied sciences, 10(8), 2829, April 2020, 18 pp.
dc.identifier.issn 2076-3417
dc.description.abstract Real-time positron emission tomography (PET) may provide information from first-shot images, enable PET-guided biopsies, and allow awake animal studies. Fully-3D iterative reconstructions yield the best images in PET, but they are too slow for real-time imaging. Analytical methods such as Fourier back projection (FBP) are very fast, but yield images of poor quality with artifacts due to noise or data incompleteness. In this work, an image reconstruction based on the pseudoinverse of the system response matrix (SRM) is presented. w. To implement the pseudoinverse method, the reconstruction problem is separated into two stages. First, the axial part of the SRM is pseudo-inverted (PINV) to rebin the 3D data into 2D datasets. Then, the resulting 2D slices can be reconstructed with analytical methods or by applying the pseudoinverse algorithm again. The proposed two-step PINV reconstruction yielded good-quality images at a rate of several frames per second, compatible with real time applications. Furthermore, extremely fast direct PINV reconstruction of projections of the 3D image collapsed along specific directions can be implemented.
dc.description.sponsorship Part of the calculations in this work were performed in the “Clúster de Cálculo para Técnicas Físicas” funded in part by UCM and in part by UE Regional Funds. We acknowledge the support from the Spanish Government (FPA2015-65035-P, RTC-2015-3772-2, and RTI2018-095800-A-I00), Comunidad de Madrid (S2013/MIT-3024 TOPUS-CM, B2017/BMD-3888 PRONTO-CM), and European Regional Funds. This work was also supported by the EU’s H2020 under MediNet, a Networking Activity of ENSAR-2 (grant agreement 654002), and by a NIH R01 CA215700-2 grant. The CNIC is supported by the Ministerio de Ciencia, Innovación y Universidades and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (SEV-2015-0505).
dc.format.extent 18
dc.language.iso eng
dc.publisher MDPI
dc.rights © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
dc.rights This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license
dc.rights Atribución 3.0 España
dc.subject.other Positron emission tomography
dc.subject.other Rebinning
dc.subject.other Real-time
dc.subject.other Image reconstruction
dc.subject.other System
dc.subject.other Matrix
dc.subject.other Pseudoinverse
dc.title Real-time 3D PET image with pseudoinverse reconstruction
dc.type article
dc.subject.eciencia Biología y Biomedicina
dc.rights.accessRights openAccess
dc.relation.projectID Comunidad de Madrid. S2013/MIT-3024
dc.relation.projectID Gobierno de España. FPA2015-65035-P
dc.relation.projectID Gobierno de España. RTC-2015-3772-2
dc.relation.projectID Gobierno de España. RTI2018-095800-A-I00
dc.relation.projectID Gobierno de España. SEV-2015-0505
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/654002/ENSAR-2
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 1
dc.identifier.publicationissue 8, 2829
dc.identifier.publicationlastpage 18
dc.identifier.publicationtitle Applied Sciences
dc.identifier.publicationvolume 10
dc.identifier.uxxi AR/0000025676
dc.contributor.funder Comunidad de Madrid
dc.contributor.funder European Commission
dc.contributor.funder Ministerio de Economía y Competitividad (España)
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