A deep neural network for positioning and inter-crystal scatter identification in multiplexed PET detectors: a simulation study.

High-resolution positron emission tomography (PET) relies on the accurate positioning of annihilation photons impinging the crystal array. However, conventional positioning algorithms in light-sharing PET detectors are often limited due to edge effects and/or the absence of additional information for identifying and correcting scattering within the crystal array (known as inter-crystal scattering). This study explores the feasibility of deep neural network (DNN) techniques for more precise event positioning in finely segmented and highly multiplexed PET detectors with light-sharing.

Virtual cylindrical PET for efficient DOI image reconstruction with sub-millimetre resolution.

Image reconstruction in high resolution, narrow bore PET scanners with depth of interaction (DOI) capability presents a substantial computational challenge due to the very high sampling in detector and image space. The aim of this study is to evaluate the use of a virtual cylinder in reducing the number of lines of response (LOR) for DOI-based reconstruction in high resolution PET systems while maintaining uniform sub-millimetre spatial resolution.Virtual geometry was investigated using the awake animal mousePET as a high resolution test case.

Multi-model sequential analysis of MRI data for microstructure prediction in heterogeneous tissue.

We propose a general method for combining multiple models to predict tissue microstructure, with an exemplar using in vivo diffusion-relaxation MRI data. The proposed method obviates the need to select a single 'optimum' structure model for data analysis in heterogeneous tissues where the best model varies according to local environment. We break signal interpretation into a three-stage sequence: (1) application of multiple semi-phenomenological models to predict the physical properties of tissue water pools contributing to the observed signal; (2) from each Stage-1 semi-phenomenological model, application of a tissue microstructure model to predict the relative volumes of tissue structure components that make up each water pool; and (3) aggregation of the predictions of tissue structure, with weightings based on model likelihood and fractional volumes of the water pools from Stage-1.

Coincidence energy spectra due to the intrinsic radioactivity of LYSO scintillation crystals.

Background: Lutetium oxyorthosilicate or lutetium yttrium oxyorthosilicate (LYSO) scintillation crystals used in most current PET scanner detectors contain Lu, which decays by beta emission to excited states of Hf accompanied by the emission of prompt gamma rays or internal conversion electrons. This intrinsic radioactivity can be self-detected in singles mode as a constant background signal that has an energy spectrum whose structure has been explained previously. In this work, we studied the energy spectrum due to the intrinsic radioactivity of LYSO scintillation crystals of two opposing detectors working in coincidence mode.