We present in this work a gamma spectrometer with real-time imaging capabilities, coupling a 3"×3" LaBr3 crystal to a 144-SiPM array. The position-sensitive spectrometer aims at state-of-the-art energy resolution and sub-centimeter spatial resolution of the gamma-photon interaction point in the scintillator, for post-processing correction of the relativistic Doppler broadening effect. The 16-channel GAMMA ASIC front-end accordingly favors a large number of 84 dB dynamic range channels integration and, in turn, the individual readout of SiPMs with accurate measurement of the scintillation light distribution. Two AI-based classifiers are trained using a collimated 137Cs source, and cascaded in the FPGA-based DAQ, achieving 1.08 cm spatial resolution with a sub-μs data latency.
Real-time Imaging with Thick LaBr3: FPGA-Embedded Machine and Deep Learning for Nuclear Physics
Buonanno, Luca;Di Vita, Davide;Ticchi, Giacomo;Canclini, Fabio;Carminati, Marco;Fiorini, Carlo
2021-01-01
Abstract
We present in this work a gamma spectrometer with real-time imaging capabilities, coupling a 3"×3" LaBr3 crystal to a 144-SiPM array. The position-sensitive spectrometer aims at state-of-the-art energy resolution and sub-centimeter spatial resolution of the gamma-photon interaction point in the scintillator, for post-processing correction of the relativistic Doppler broadening effect. The 16-channel GAMMA ASIC front-end accordingly favors a large number of 84 dB dynamic range channels integration and, in turn, the individual readout of SiPMs with accurate measurement of the scintillation light distribution. Two AI-based classifiers are trained using a collimated 137Cs source, and cascaded in the FPGA-based DAQ, achieving 1.08 cm spatial resolution with a sub-μs data latency.File | Dimensione | Formato | |
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Real-time Imaging with Thick LaBr3 FPGA-Embedded Machine and Deep Learning for Nuclear Physics - NSS 2021.pdf
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