Inter-crystal scattering recovery of light-sharing PET detectors using convolutional neural networks

Resolving inter-crystal scatter in a light-sharing depth-encoding PET detector

Objective.Inter-crystal scattering (ICS) in light-sharing positron emission tomography (PET) detectors leads to ambiguity in positioning the initial interaction, which significantly degrades the contrast, quantitative accuracy, and spatial resolution of the resulting image. Here, we attempt to resolve the positioning ambiguity of ICS in a light-sharing depth-encoding detector by exploiting the confined, deterministic light-sharing enabled by the segmented light guide unique to Prism-PET.Approach.We first considered a test case of ICS between two adjacent crystals using an analytical and a neural network approach. The analytical approach used a Bayesian estimation framework constructed from a scatter absorption model-the prior-and a detector response model-the likelihood. A simple neural network was generated for the same scenario, to provide mutual validation for the findings. Finally, we generalized the solution to three-dimensional event positioning that handles all events in the photopeak using a convolutional neural network with unique architecture that separately predicts the identity and depth-of-interaction (DOI) of the crystal containing the first interaction.Main results.The analytical Bayesian method generated an estimation error of 20.5 keV in energy and 3.1 mm in DOI. Further analysis showed that the detector response model was sufficiently robust to achieve adequate performance via maximum likelihood estimation (MLE), without prior information. We then found convergent results using a simple neural network. In the generalized solution using a convolutional neural network, we found crystal identification accuracy of 83% and DOI estimation error of 3.0 mm across all events. Applying this positioning algorithm to simulated data, we demonstrated significant improvements in image quality over the baseline, centroid-based positioning approach, attaining 38.9% improvement in intrinsic spatial resolution and enhanced clarity in hot spots of diameters 0.8 to 2.5 mm.Significance.The accuracy of our findings exceeds those of previous reports in the literature. The Prism-PET light guide, mediating confined and deterministic light-sharing, plays a key role in ICS recovery, as its mathematical embodiment-the detector response model-was the essential driver of accuracy in our results.

A multi-resolution TOF-DOI detector for human brain dedicated PET scanner

Objective. We propose a single-ended readout, multi-resolution detector design that can achieve high spatial, depth-of-interaction (DOI), and time-of-flight (TOF) resolutions, as well as high sensitivity for human brain-dedicated positron emission tomography (PET) scanners.Approach. The detector comprised two layers of LYSO crystal arrays and a lightguide in between. The top (gamma ray entrance) layer consisted of a 16 × 16 array of 1.53 × 1.53 × 6 mm3LYSO crystals for providing high spatial resolution. The bottom layer consisted of an 8 × 8 array of 3.0 × 3.0 × 15 mm3LYSO crystals that were one-to-one coupled to an 8 × 8 multipixel photon counter (MPPC) array for providing high TOF resolution. The 2 mm thick lightguide introduces inter-crystal light sharing that causes variations of the light distribution patterns for high DOI resolution. The detector was read out by a PETsys TOFPET2 application-specific integrated circuit.Main result. The top and bottom layers were distinguished by a convolutional neural network with 97% accuracy. All crystals in the top and bottom layers were resolved. The inter-crystal scatter (ICS) events in the bottom layer were identified, and the measured average DOI resolution of the bottom layer was 4.1 mm. The coincidence time resolution (CTR) for the top-top, top-bottom, and bottom-bottom coincidences was 476 ps, 405 ps, and 298 ps, respectively. When ICS events were excluded from the bottom layer, the CTR of the bottom-bottom coincidence was 277 ps.Significance. The top layer of the proposed two-layer detector achieved a high spatial resolution and the bottom layer achieved a high TOF resolution. Together with its high DOI resolution and detection efficiency, the proposed detector is well suited for next-generation high-performance brain-dedicated PET scanners.

Advancements in Positron Emission Tomography Detectors: From Silicon Photomultiplier Technology to Artificial Intelligence Applications

This review article focuses on PET detector technology, which is the most crucial factor in determining PET image quality. The article highlights the desired properties of PET detectors, including high detection efficiency, spatial resolution, energy resolution, and timing resolution. Recent advancements in PET detectors to improve these properties are also discussed, including the use of silicon photomultiplier technology, advancements in depth-of-interaction and time-of-flight PET detectors, and the use of artificial intelligence for detector development. The article provides an overview of PET detector technology and its recent advancements, which can significantly enhance PET image quality.

Joint estimation of interaction position and energy deposition in semiconductor SPECT imaging sensors using fully connected neural network

Objective.Pixelated semiconductor detectors such as CdTe and CZT sensors suffer spatial resolution and spectral performance degradation induced by charge-sharing effects. It is critical to enhance the detector property through recovering the energy-deposition and position estimation.Approach.In this work, we proposed a fully-connected-neural-network-based charge-sharing reconstruction algorithm to correct the charge-loss and estimate the sub-pixel position for every multi-pixel charge-sharing event.Main results.Evident energy resolution improvement can be observed by comparing the spectrum produced by a simple charge-sharing addition method and the proposed energy correction methods. We also demonstrate that sub-pixel resolution can be achieved in projections obtained with a small pinhole collimator and an innovative micro-ring collimator.Significance.These achievements are crucial for multiple-tracer SPECT imaging applications, and for other semiconductor detector-based imaging modalities.

Silicon photomultiplier signal readout and multiplexing techniques for positron emission tomography: a review

In recent years, silicon photomultiplier (SiPM) is replacing the photomultiplier tube (PMT) in positron emission tomography (PET) systems due to its superior properties, such as fast single-photon timing response, small gap between adjacent photosensitive pixels in the array, and insensitivity to magnetic fields. One of the technical challenges when developing SiPM-based PET systems or other position-sensitive radiation detectors is the large number of output channels coming from the SiPM array. Therefore, various signal multiplexing methods have been proposed to reduce the number of output channels and the load on the subsequent data acquisition (DAQ) system. However, the large PN-junction capacitance and quenching resistance of the SiPM yield undesirable resistance–capacitance delay when multiple SiPMs are combined, which subsequently causes the accumulation of dark counts and signal fluctuation of SiPMs. Therefore, without proper SiPM signal handling and processing, the SiPMs may yield worse timing characteristics than the PMTs. This article reviews the evolution of signal readout and multiplexing methods for the SiPM. In this review, we focus primarily on analog electronics for SiPM signal multiplexing, which allows for the reduction of DAQ channels required for the SiPM-based position-sensitive detectors used in PET and other radiation detector systems. Although the applications of most technologies described in the article are not limited to PET systems, the review highlights efforts to improve the physical performance (e.g. spatial, energy, and timing resolutions) of PET detectors and systems.