Position estimation using neural networks in semi-monolithic PET detectors.
Phys Med Biol
; 67(24)2022 12 09.
Article
en En
| MEDLINE
| ID: mdl-36384047
ABSTRACT
Objective. The goal of this work is to experimentally compare the 3D spatial and energy resolution of a semi-monolithic detector suitable for total-body positron emission tomography (TB-PET) scanners using different surface crystal treatments and silicon photomultiplier (SiPM) models.Approach. An array of 1 × 8 lutetium yttrium oxyorthosilicate (LYSO) slabs of 25.8 × 3.1 × 20 mm3separated with Enhanced Specular Reflector (ESR) was coupled to an array of 8 × 8 SiPMs. Three different treatments for the crystal were evaluated ESR + RR + B,with lateral faces black (B) painted and a retroreflector (RR) layer added to the top face; ESR +RR, with lateral faces covered with ESR and a RR layer on the top face and; All ESR, with lateral and top sides with ESR. Additionally, two SiPM array models from Hamamatsu Photonics belonging to the series S13361-3050AE-08 (S13) and S14161-3050AS-08 (S14) have been compared. Coincidence data was experimentally acquired using a22Na point source, a pinhole collimator, a reference detector and moving the detector under study in 1 mm steps in thex- andDOI- directions. The spatial performance was evaluated by implementing a neural network (NN) technique for the impact position estimation in thex- (monolithic) andDOIdirections.Results. Energy resolution values of 16 ± 1%, 11 ± 1%, 16 ± 1%, 15 ± 1%, and 13 ± 1% were obtained for theS13-ESR + B + RR,S13-AllESR,S14-ESR + B + RR,S14-ESR + RR,andS14-AllESR, respectively. Regarding positioning accuracy, mean average error of 1.1 ± 0.5, 1.3 ± 0.5 and 1.3 ± 0.5 were estimated for thex- direction and 1.7 ± 0.8, 2.0 ± 0.9 and 2.2 ± 1.0 for theDOI- direction, for the ESR + B + RR, ESR + RR and All ESR cases, respectively, regardless of the SiPM model.Significance. Overall, the obtained results show that the proposed semi-monolithic detectors are good candidates for building TB-PET scanners.
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1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Redes Neurales de la Computación
/
Tomografía de Emisión de Positrones
Idioma:
En
Revista:
Phys Med Biol
Año:
2022
Tipo del documento:
Article
País de afiliación:
España