Feb 21 – 25, 2022
Vienna University of Technology
Europe/Vienna timezone

Embedded Artificial Intelligence for Position Sensitivity in Thick Scintillators

Not scheduled
Vienna University of Technology

Vienna University of Technology

Gusshausstraße 27-29, 1040 Wien
Recorded Presentation SiPM


Mr Giacomo Ticchi (Politecnico di Milano)


This research work consists in the design, development, and experimental characterization of a γ-ray spectrometer based on large lanthanum bromide scintillator crystals (3” × 3”) coupled with SiPMs. In nuclear physics experiments where photon’s energy ranges from 100 keV to 30 MeV, GAMMA provides state-of-the-art energy resolution (<3% at 662 keV) with a compact, modular and robust structure.

The interaction position reconstruction in the crystal volume is a fundamental information to compensate the Relativistic Doppler effect which leads to an undesired energy shift of the measured photon’s energy. To accomplish this task, imaging capabilities have been implemented on GAMMA: different Artificial Intelligence algorithms such as Decision Trees and Neural Networks have been tested. Results about 1-D and 2-D position sensitivity will be shown explaining how an RMS-Error lower than 1.5 cm$_{rms}$ has been met on the 2-D reconstruction; furthermore, an estimate of the DOI in such a thick scintillator will be presented.

Finally, Artificial Intelligence algorithms have been synthesized in an FPGA to allow Real Time position sensitivity. Important results about latency and percentage of hardware resources used (DSP, LUT) will be discussed comparing Decision Tree and Neural Network solutions.

Primary authors

Mr Giacomo Ticchi (Politecnico di Milano) Dr Luca Buonanno (Politecnico di Milano) Dr Davide Di Vita (Politecnico di Milano) Dr Fabio Canclini (Politecnico di Milano) Prof. Carminati Marco (Politecnico di Milano) Prof. Franco Camera (Università degli Studi di Milano) Prof. Carlo Fiorini (Politecnico di Milano)

Presentation materials