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Monte Carlo evaluation of a LYSO‐based Compton camera using two origin ensemble algorithms with resolution recovery
Author(s) -
Huang HsuanMing
Publication year - 2021
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.15092
Subject(s) - lyso , algorithm , imaging phantom , image resolution , monte carlo method , bragg peak , physics , computer science , artificial intelligence , beam (structure) , optics , mathematics , detector , statistics , scintillator
Purpose Due to the lack of depth‐of‐interaction information, a Compton camera made of lutetium‐yttrium orthosilicate (LYSO) crystals suffers from poor spatial resolution, which may lead to an unreliable range verification in proton therapy. The aim of this study is to evaluate the performance of a LYSO‐based Compton camera using the origin ensemble algorithm with resolution recovery (OE‐RR). We also proposed a regularized version of OE‐RR called ROE‐RR. Methods We simulated a two‐layer LYSO‐based Compton camera which was used to detect prompt gammas (PGs) produced by a proton beam irradiated on a water phantom. PG images reconstructed by the OE‐RR algorithm were evaluated and compared with those reconstructed by the proposed ROE‐RR algorithm. Results Our simulated results show that both the OE‐RR and ROE‐RR algorithms could provide an accurate estimate of the Bragg peak position, with a mean positioning error of 2.5 mm. Compared to the OE‐RR algorithm, the proposed ROE‐RR algorithm is less sensitive with respect to initial conditions and requires less iterations for converging to equilibrium. More importantly, the proposed ROE‐RR algorithm could provide better image quality than the OE‐RR algorithm, especially in low‐count data. Conclusions For LYSO‐based Compton cameras, using a resolution‐recovery image reconstruction algorithm is essential for reliable range verification.