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Ensemble of neural networks for 3D position estimation in monolithic PET detectors

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Ensemble of neural networks for 3D position estimation in monolithic PET detectors

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dc.contributor.author Iborra Carreres, Amadeo es_ES
dc.contributor.author González Martínez, Antonio Javier es_ES
dc.contributor.author González, A. es_ES
dc.contributor.author Bousse, A. es_ES
dc.contributor.author Visvikis, Dimitris es_ES
dc.date.accessioned 2020-05-30T03:30:51Z
dc.date.available 2020-05-30T03:30:51Z
dc.date.issued 2019-10-04 es_ES
dc.identifier.issn 0031-9155 es_ES
dc.identifier.uri http://hdl.handle.net/10251/144674
dc.description.abstract [EN] We propose an ensemble of multilayer feedforward neural networks to estimate the 3D position of photoelectric interactions in monolithic detectors. The ensemble is trained with data generated from optical Monte Carlo simulations only. The originality of our approach is to exploit simulations to obtain reference data, in combination with a variability reduction that the network ensembles offer, thus, removing the need of extensive per-detector calibration measurements. This procedure delivers an ensemble valid for any detector of the same design. We show the capability of the ensemble to solve the 3D positioning problem through testing four different detector designs with Monte Carlo data, measurements from physical detectors and reconstructed images from the MindView scanner. Network ensembles allow the detector to achieve a 2-2.4 mm FWHM, depending on its design, and the associated reconstructed images present improved SNR, CNR and SSIM when compared to those based on the MindView built-in positioning algorithm. es_ES
dc.language Inglés es_ES
dc.publisher IOP Publishing es_ES
dc.relation.ispartof Physics in Medicine and Biology es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Positron-emission tomography es_ES
dc.subject Monolithic PET detectors es_ES
dc.subject Ensemble of neural networks es_ES
dc.subject Monte Carlo generated training es_ES
dc.subject Interaction position determination es_ES
dc.subject Depth of interaction determination es_ES
dc.title Ensemble of neural networks for 3D position estimation in monolithic PET detectors es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1088/1361-6560/ab3b86 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/603002/EU/Multimodal Imaging of Neurological Disorders/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Instrumentación para Imagen Molecular - Institut d'Instrumentació per a Imatge Molecular es_ES
dc.description.bibliographicCitation Iborra Carreres, A.; González Martínez, AJ.; González, A.; Bousse, A.; Visvikis, D. (2019). Ensemble of neural networks for 3D position estimation in monolithic PET detectors. Physics in Medicine and Biology. 64(19):1-20. https://doi.org/10.1088/1361-6560/ab3b86 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1088/1361-6560/ab3b86 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 20 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 64 es_ES
dc.description.issue 19 es_ES
dc.identifier.pmid 31416053 es_ES
dc.relation.pasarela S\406055 es_ES
dc.contributor.funder European Commission es_ES
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