Extending gPET for Multi-Layer PET Simulation
Satzhan Sitmukhambetov, Junwei Du, Mingwu Jin, Yujie Chi

TL;DR
This paper extends the GPU-accelerated gPET toolkit to support multi-layer detector geometries, enabling efficient simulation and optimization of DOI-capable PET systems with improved spatial resolution.
Contribution
The authors introduce a new multi-layer detector modeling capability in gPET, allowing flexible simulation of complex PET detector architectures with minimal performance impact.
Findings
Multi-layer configurations produce expected interaction patterns.
Sensitivity remains comparable across configurations.
Radial spatial resolution improves significantly with dual-layer design.
Abstract
Depth-of-interaction (DOI) encoding is an effective strategy for reducing parallax error and preserving spatial resolution in positron emission tomography (PET), particularly in compact small-animal scanners. To enable efficient simulation-driven design of DOI-capable systems, we extend the GPU-accelerated Monte Carlo toolkit gPET to support flexible multi-layer detector geometries. The original three-level hierarchical detector model in gPET (panel-module-crystal) was expanded by introducing an intermediate "layer" level, enabling parameterized modeling of stacked scintillator architectures. The photon transport algorithm was correspondingly updated to sample interactions across multiple layers and detector panels while preserving GPU-efficient memory usage. The framework was validated using three scanner configurations: a conventional single-layer ring (H2RSPET-1CL), an aligned…
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Taxonomy
TopicsMedical Imaging Techniques and Applications · Radiation Detection and Scintillator Technologies · Particle Detector Development and Performance
