RT Journal Article
T1 Reconstruction of multi-animal PET acquisitions with anisotropically variant PSF
A1 Arias Valcayo, Fernando
A1 Galve Lahoz, Pablo
A1 López Herraiz, Joaquín
A1 Vaquero, J J
A1 Desco, M
A1 Udías Moinelo, José Manuel
AB Among other factors such as random, attenuation and scatter corrections, uniform spatial resolution is key to performing accurate quantitative studies in Positron emission tomography (PET). Particularly in preclinical PET studies involving simultaneous acquisition of multiple animals, the degradation of image resolution due to the depth of interaction (DOI) effect far from the center of the Field of View (FOV) becomes a significant concern. In this work, we incorporated a spatially-variant resolution model into a real time iterative reconstruction code to obtain accurate images of multi-animal acquisition. We estimated the spatially variant point spread function (SV-PSF) across the FOV using measurements and Monte Carlo (MC) simulations. The SV-PSF obtained was implemented in a GPU-based Ordered subset expectation maximization (OSEM) reconstruction code, which includes scatter, attenuation and random corrections. The method was evaluated with acquisitions from two preclinical PET/CT scanners of the SEDECAL Argus family: a Derenzo phantom placed 2 cm off center in the 4R-SuperArgus, and a multi-animal study with 4 mice in the 6R-SuperArgus. The SV-PSF reconstructions showed uniform spatial resolution without significant increase in reconstruction time, with superior image quality compared to the uniform PSF model.
PB IOP Publishing
YR 2023
FD 2023-10-16
LK https://hdl.handle.net/20.500.14352/134704
UL https://hdl.handle.net/20.500.14352/134704
LA eng
NO Arias-Valcayo, F., Galve, P., Herraiz, J. L., Vaquero, J. J., Desco, M., & Udías, J. M. (2023). Reconstruction of multi-animal PET acquisitions with anisotropically variant PSF. Biomedical Physics & Engineering Express, 9(6), 065018.
NO ©2023 ©2022 IOP Publishing Ltd.
NO Agencia Estatal de Investigación (España)
NO Ministerio de Ciencia Innovación y Universidades (España)
NO European Commission
NO Instituto de Salud Carlos III (España)
NO Comunidad de Madrid
NO Universidad Complutense de Madrid
DS Docta Complutense
RD 27 abr 2026