Imaging Detector Research Articles

Feasibility Study of a PET Detector with a Wavelength-Shifting Fiber Readout

We designed and evaluated the performance of a high-resolution large-area detector for positron emission tomography (PET) based on a crystal assembly readout using wavelength-shifting (WLS) fibers, offering a cost-effective alternative to the direct readout of monolithic crystals with photodetectors. The considered detector geometries were made up of 4 × 4 assemblies of LuY2SiO5:Ce (LYSO) crystal scintillators, each with surface area of 50 × 50 mm2 and thickness of 7 or 15 mm, which were optically coupled together using optical adhesive. The crystal assembly was coupled with square cross-sections of orthogonal wavelength-shifting (WLS) fibers placed on the top and bottom of the assembly. To evaluate the characteristics of the novel detector, we used GEANT4 to perform optical photon transport in the crystal assembly and WLS fibers. The simulation results show that best position resolution achieved was 1.6 ± 0.4 mm full width at half maximum (FWHM) and 4.2 ± 0.6 mm full width at tenth maximum (FWTM) for the crystal thickness of 7 mm and 1.7 ± 0.4 mm FWHM and 6.0 ± 0.6 mm FWTM for the crystal thickness of 15 mm. Compared with a direct photosensor readout, WLS fibers can drastically reduce the number of photosensors required while covering a larger sensitive detection area. In the proposed detector design, 2N photodetectors are used to cover the same image area instead of N2 with a direct readout. This design allows for the development of a compact detector with an expanded effective field of view and reduced cost.

Study on enhancement of imaging effect of silicon-based up-conversion NIR detector by cascade material fusion method

The nonlinear frequency conversion of the up-conversion materials facilitates the conversion of near-infrared (NIR) into visible, which can be detected by the silicon-based detector. However, the low emission intensity of up-conversion materials limited the application. In this paper, a cascade material fusion (CMF) method was proposed to increase the visible emission intensity, which enhanced the imaging of up-conversion silicon-based NIR detectors. The energy level transition mechanism of CMF suggested that the host material (HM) could realize four stimulated emissions under 1550 nm excitation to enhance the up-conversion emission intensity of HM. The silicon-based NIR imaging detectors based on CMF and HM were prepared, and it was observed that the fusion ratio of doped material (DM) and HM has a significant impact on the silicon-based NIR imaging detector upon 1550 nm excitation. The enhanced imaging effect was optimal when the fusion ratio of DM and HM was 0.125, which enhanced about 3.4 times by comparison with the HM detector.

New robotic tools for multimodal non-destructive analysis and characterization of 2D and 3D objects

The forensic field has until now been missing more versatile equipment for non-destructive characterization, analysis and inspection of 2D and 3D objects. Also, the need for increasingly frequent analysis of art forgeries, where non-destructive analysis is required at least in the first step, is calling for a multimodal solution. A prototype device for robotic analysis, imaging and mapping of 3D objects is being developed and tested to be used in these areas. The system is based on the principle of integrating imaging and analytical technologies onto six-axis robotic arms, which allow substantial flexibility in the sample size or shape. The system enables non-destructive examination of a wide spectrum of samples with complicated curvatures. The new generation of X-ray imaging detectors provide a high picture quality with a spatial resolution level in the micrometre range in 2D or 3D imaging. The basic version of the robotic scanner allows transmission X-ray imaging and mapping of the individual photons with high-sensitivity and high-resolution detectors. The broad capabilities of XRD imaging are now being complemented by X-ray fluorescence point analysis and mapping, multispectral macro imaging, and multispectral X-ray diffraction analysis.

Analyzing the Impact of Over Speeding of the Vehicles in the Society

Over-speeding is a leading cause of business accidents, performing in significant losses and severe injuries worldwide. According to WHO, speed is a contributing factor in roughly 30 of road deaths in high- income countries and nearly 50 in lowand middle- income countries. Controlling vehicle speed is pivotal to precluding crashes and minimizing the inflexibility of injuries. Traditional styles of speed control and business law enforcement are frequently shy in effectively managing and reducing over-speeding incidents. To address this issue, recent studies have explored colorful technological results, similar as the Automatic E-Challan System, IOT- grounded business violation systems, and RF- grounded vehicle discovery. These systems use advanced technologies like detector networks, image processing, and radio frequence to cover business, descry violations, and issue penalties automatically. These approaches aim to enhance enforcement effectiveness, ameliorate business operation, and reduce road accidents. Our exploration focuses on integrating an automated speed discovery system that not only cautions motorists when they exceed speed limits but also contributes to reducing road accidents by administering compliance with business regulations. This result is anticipated to ameliorate road safety by precluding over-speeding and icing timely interventions.

A magnetic field compatible readout circuit for enhanced coincidence time resolution in BGO Cherenkov radiation-based TOF-PET detectors.

Developing time-of-flight positron emission tomography/magnetic resonance imaging (TOF-PET/MRI) detectors that exploit prompt Cherenkov photons from bismuth germanate (BGO) crystals for estimating 511keV photon arrival time. To present a low-noise, high-speed electronic readout circuit design for BGO-based TOF-PET detectors that achieves enhanced coincidence time resolution (CTR) in presence of a strong magnetic field. The CTR of a BGO-based TOF-PET test detector employing a high-speed, low-noise electronic readout chain was evaluated in a strong magnetic field produced by a permanent magnet placed directly on top of the circuit. For these experiments, which exploit Cherenkov radiation for precise measurement of annihilation photon time arrival time difference, a point source of 22Na was positioned between a pair of 3×3×15mm3 polished BGO crystals wrapped in Teflon tape and optically coupled to 3×3mm2 ultra-violet (UV)-sensitive silicon photomultipliers (SiPMs). By incorporating both Cherenkov (prompt) and standard (slow) luminescence components, 283±8ps and 275±10ps full-width-half-maximum(FWHM) CTR were achieved without and with the permanent magnet present, respectfully. These values improved to 236±4ps and 216±17ps FWHM when only the Cherenkov components of the timing signal (events with the fastest rise time) were considered. Results indicate we have designed a high-performance readout circuit that achieves significantly the same CTR in BGO with or without a strong magnetic field present. This further demonstrates that UV SiPMs can effectively operate in a strong magnetic field while remaining highly advantageous for detecting Cherenkov radiation, thus highlighting their potential to be used in BGO-based TOF-PET/MRI scanners.

Using the STIX background detector as a proxy for GOES

The Spectrometer/Telescope for Imaging X-Rays (STIX) on board Solar Orbiter was designed to observe solar flares in the X-ray range of 4-150 keV, providing spectral, temporal, and spatial information. Besides 30 imaging detectors, STIX has two additional detectors: the coarse flare locator (CFL) and the background (BKG) detector, which are used in the present study. Flares observed from Earth are classified using their peak X-ray flux observed by the Geostationary Operational Environmental Satellite (GOES) instruments. Given to the Solar Orbiter mission design, roughly half of all flares observed by STIX are located on the backside of the Sun. These flares lack a GOES-class classification. In this paper, we describe the calibration of the BKG detector aperture sizes. Using the calibrated measurements of the BKG detector, we explore the relationship between the peak flux for flares jointly observed by STIX and GOES. This allows us to estimate the GOES flare classes of backside flares using STIX measurements. We looked at the 500 largest flares observed by both STIX and GOES in the time range February 2021 to April 2023. The aperture size calibration was done by comparing 4-10 keV counts of the BKG detector with the CFL measurements. In a second step, we correlated the calibrated STIX BKG peak flux with the GOES peak flux for individual flares. We calibrated the BKG detector aperture sizes of STIX, which are now ready to be implemented into the ground-software (GSW) of STIX. Furthermore, we showed that for the larger flares (C class and above) a close power law fit exists between the STIX BKG and GOES peak flux, with a Pearson correlation coefficient of 0.97. This correlation provides a GOES proxy with a one sigma uncertainty of ≈ 11%. We were able to show that the BKG detector can reliably measure a broad range of GOES flare classes from roughly B5 up to at least X85 (assuming a radial distance of 1AU). This makes it an interesting detector-concept for future space weather missions. Thus far, the largest flare observed by STIX to date is an estimated X16.5 ± 1.8 backside flare of May 20, 2024.

Evaluasi Exposure Index (EI) Pada Pemeriksaan Radiografi Thorax Posterior-Anterior (PA): Cross-Sectional Study

Chest Posterior-Anterior (PA) radiographic examination is a medical imaging using ionizing radiation to obtain patient diagnostic information. In digital radiographic medical imaging techniques, an indicator shows the radiographic image detector (imaging plate) response to radiation exposure, which is called the exposure index (EI). Therefore, in applying radiation dose optimization in the PA thorax radiographic examination procedure it is necessary to evaluate to determine the indicators of underexposure, optimal exposure, and overexposure exposure. The research method used is quantitative descriptive with cross-sectional study. This research was carried out between March-May 2023 using 70 radiographic examination samples. Then evaluate the percentage of the use of exposure indicators. After that, perform statistical analysis using SPSS IBM25 with Kendall's tau-b test to determine the level of correlation between the use of exposure factors and EI. The results of the study of 70 patients showed an indicator of overexposure of 67% and optimal exposure of 33%. Meanwhile, the results of Kendall's tau-b test showed no correlation between the exposure factor variabel and EI. This shows that using EI as an optimization is not enough to know the exposure factor, but complete radiographic examination procedure data is needed.

Centimeter-Sized CsPbBr3 Single-Crystal Films for Energy-Resolved Radiation Detection.

Metal halide perovskites (MHPs) are promising materials for radiation detection. Compared with polycrystalline films, single crystals (SCs) have lower defect density, higher carrier mobility, and lifetime. However, the direct synthesis of MHP SCs for large-area flat panel imaging detectors remains challenging. Here, we show that high-quality centimeter-sized CsPbBr3 SCs with thicknesses between 0.25 mm and 1 mm can be grown by a space-confined inverse temperature method. The addition of choline bromide to the precursor solution reduces the defect density and suppresses ion migration of the CsPbBr3 SCs, leading to a high resistivity of 2.5 × 1010 Ω cm and a high mobility-lifetime product of over 1 × 10-3 cm2 V-1. The CsPbBr3 SC spectral detectors exhibit an energy resolution of 14.96% for 241Am 59.5 keV X-ray and 15.95% for 5.48 MeV α-particles. Moreover, a prototype 3 × 3 pixelated detector based on the large-area SC shows a consistent high performance for all pixels, making it promising for high-resolution flat panel imaging detectors.

FLAME: fire detection in videos combining a deep neural network with a model-based motion analysis

Abstract Among the catastrophic natural events posing hazards to human lives and infrastructures, fire is the phenomenon causing more frequent damages. Thanks to the spread of smart cameras, video fire detection is gaining more attention as a solution to monitor wide outdoor areas where no specific sensors for smoke detection are available. However, state-of-the-art fire detectors assure a satisfactory Recall but exhibit a high false-positive rate that renders the application practically unusable. In this paper, we propose FLAME, an efficient and adaptive classification framework to address fire detection from videos. The framework integrates a state-of-the-art deep neural network for frame-wise object detection, in an automatic video analysis tool. The advantages of our approach are twofold. On the one side, we exploit advances in image detector technology to ensure a high Recall. On the other side, we design a model-based motion analysis that improves the system’s Precision by filtering out fire candidates occurring in the scene’s background or whose movements differ from those of the fire. The proposed technique, able to be executed in real-time on embedded systems, has proven to surpass the methods considered for comparison on a recent literature dataset representing several scenarios. The code and the dataset used for designing the system have been made publicly available by the authors at (https://mivia.unisa.it/large-fire-dataset-with-negative-samples-lfdn/).

3D integration of pixel readout chips using Through-Silicon-Vias

Particle tracking and imaging detectors are becoming increasingly complex, driven by demands for densely integrated functionality and maximal sensitive area. These challenging requirements can be met using 3D interconnect techniques widely used in industry. In this paper, we present the results of an evaluation of the 3D Through-Silicon-Via (TSV) technology, using the Timepix4 integrated circuit as a test-vehicle. We will present the concepts for 3D integration and test results from TSV-processed chips bonded to custom-designed circuit boards conceived as proofs-of-principle for future detector modules.

GRAPH — an readout ASIC for large MCP based detectors

We present a programmable 16 channel, mixed signal, low power readout ASIC, having the project historically named Gigasample Recorder of Analog waveforms from a PHotodetector (GRAPH). It is designed to read large aperture single photon imaging detectors using micro channel plates for charge multiplication, and measuring the detector's response on crossed strips anodes to extrapolate the incoming photon position. Each channel consists of a fast, low power and low noise charge sensitive amplifier, which provides a myriad of coarse and fine programmable options for gain and shaping settings. Further, the amplified signal is recorded using, to our knowledge novel, the Hybrid Universal sampLing Architecture (HULA) ADC. A kind of mixed signal double buffer memory, that enables concurrent waveform recording, and selected event digitized data extraction. The sampling frequency is freely adjustable between few kHz up to 125 MHz, while the chip's internal digital memory holds a history 2048 samples for each channel, with a digital headroom of 12 bits. An optimized region of interest sample-read algorithm allows to extract the information just around the event pulse peak, while selecting the next event, thus substantially reducing the operational dead time. The chip is designed in 130 nm TSMC CMOS technology, and its power consumption is around 47 mW per channel.

Assessing the dosimetric effects of high-Z titanium implants in proton therapy using pixel detectors

A rapid increase in the use of proton therapy for cancer treatment has been seen in the last decade due to its clinical advantages. Therefore, more and more patients with implants and other metallic devices will be among those who will be treated. This study experimentally examines the effect and changes in the delivered fields, using water-equivalent phantoms with and without titanium (Ti) dental implants positioned along the primary beam path. We measured in detail the composition and spectral-tracking characterization of particles generated in the plateau region of the Bragg curve towards the Sub-peak region using high-spatial resolution, spectral and time-sensitive imaging detectors with a pixelated array provided by the ASIC chip Timepix3. A 170 MeV proton beam was collimated and modulated in a polymethyl methacrylate (PMMA) block. Placing two dental implants behind the PMMA block, the radiation was measured using two pixeled detectors with silicon (Si) sensors. The Timepix3 (TPX3) detectors measured in detail particle fluxes, dose rates (DR) and linear energy transfer (LET) spectra for resolved particle types. Artificial intelligence (AI) based-trained neural networks (NN) calibrated in well-defined radiation fields were used to analyze and identify particles based on morphology and characteristic spectral-tracking response. The beam was characterized and single-particle tracks were registered and decomposed into particle-type groups. The resulting particle fluxes in both setups are resolved into three main classes of particles: i) protons, ii) electrons and photons, and iii) ions. Protons are the main particle component responsible for dose deposition. High-energy transfer particles (HETP), namely ions exhibited differences in both dosimetric aspects that were investigated: DR and particle fluxes, when the Ti implants were placed in the setup. The detailed multi-parametric information of the secondary radiation field provides a comprehensive understanding of the impact of Ti materials in proton therapy.

Development of Two-Layer Depth-of-Interaction Detector for Small Animal Positron Emission Tomography(PET)/Magnetic Resonance Imaging (MRI) through Photoelectric Peak Analysis

Development of Two-Layer Depth-of-Interaction Detector for Small Animal Positron Emission Tomography(PET)/Magnetic Resonance Imaging (MRI) through Photoelectric Peak Analysis

Energy-resolved fast-neutron radiography using an event-mode neutron imaging detector

Energy-resolved fast-neutron radiography is a powerful non-destructive technique that can be used to remotely measure the quantity and distribution of elements and isotopes in a sample. This is done by comparing the energy-dependent neutron transmission of a sample with the known cross-sections of individual isotopes. The reconstruction of the composition is possible due to the unique features (e.g. resonances) in the cross-sections of individual isotopes. At short-pulsed ( 1 ns) neutron sources, such information is accessible via time-of-flight neutron imaging in principle, but requires a detector with nanosecond temporal resolution. Conventional neutron detectors can meet this requirement only by heavily compromising spatial resolution or efficiency. Here, we present a unique approach on fast neutron resonance radiography using a scintillator-based event-mode imaging detector at a short-pulsed neutron source, including first results on spatially mapped resonance profiles using MeV neutrons. The event mode approach applied in the presented detector allows recording of individual neutron interactions with nanosecond precision in time and sub-mm resolution in space. As a result, the entire available neutron energy spectrum can be measured for each pulse. At the same time, the use of a thick scintillator screen and lenses to focus the produced light results in a highly flexible field of view and a high interaction probability in the sensitive volume of the detector.

LumaCam: a novel class of position-sensitive event mode particle detectors using scintillator screens.

A new type of position-sensitive detectors is gaining attention in the neutron community. They are scintillator based detectors that detect the scintillation light on an individual photon basis via an image intensifier and a fast image sensor. Their readout operates in event mode i.e. it produces information about individual neutron interactions, reconstructed from the sensor data, thus enabling to achieve superior spatial and temporal resolutions compared to regular detectors. Although the development of current detectors is focused on neutrons, the concept is also applicable to the detection of other particles such as high-energy photons. This document provides a description on how these detectors are built, how they operate, and what their characteristics are. An example of a detector implementation based on a Timepix3 chip is described to illustrate the detector concept. This includes a detailed description of the algorithm that reconstructs the neutron interactions from the sensor data, one of the core components that sets it apart from established scintillator-based imaging detectors. Energy-resolved epithermal neutron radiography was performed at the ISIS EMMA beamline with this detector, illustrating some of the fundamental differences in the data that can be produced with the new type of detector compared to more established types of scintillator based neutron detectors. The term LumaCam is proposed to refer to this new class of position-sensitive event-mode detectors.

Unfolding X-Ray Spectral Data: Conditions and Applications

We present conditions for which X-ray spectra can be “unfolded” to present an accurate representation of the true source spectra. The method we use to unfold the data is implemented in the Interactive Spectral Interpretation Software and distinguishes itself as being model-independent. We find that this method of unfolding makes accurate representations of the true source spectra: (1) The detector is high-resolution, and (2) The spectrum is not steeply sloped. These criteria are not simple conditions that give concrete determinations; each detector and spectrum must be judged individually. We find that both grating and imaging detectors can be unfolded with minimal distortions as compared to both continuum and local spectral features, the latter CCD detectors being much more energy dependent. We also provide example use cases for unfolding in the context of current generation X-ray observatories and important caveats.

Design and implementation of the first proton beam transport line in VEGA-3 Petawatt laser system

Laser–Plasma ion acceleration is acquiring importance on a daily basis due to incipient applicability in certain research fields. However, the energy and divergence control of these brilliant sources can be considered a bottleneck in the development of some applications. In this work, we present the commissioning of a compact proton beamline based on a triplet of quadrupoles dedicated to focus and collect short and energetic pulses, open to the user community. The focused proton beam characterization has been carried out by imaging of scintillation detectors with different particle filters. Experimental results have been compared with numerical simulations performed with Monte Carlo code (MCNP6) and TSTEP that have been used to retrieve the deposited energy, the particle tracking, and the particle distribution in different focal configurations, respectively. Charges of nC ( protons with energies up to 17.25 MeV) have been measured at the focal planes reducing the beam to spot sizes of a few millimetres in RMS (root mean square). The percentage fluctuation of the transported charges values has been studied. Finally, the beam rigidity has been measured by transverse moving of the quadrupoles and subsequent beam centroid shift, allowing to cross correlate the deflected energy with the energy ranges resulting from the filtering process.

An Ecologist-Friendly R Workflow for Expediting Species-Level Classification of Camera Trap Images.

Camera trapping has become increasingly common in ecological studies, but is hindered by analyzing large datasets. Recently, artificial intelligence (deep learning models in particular) has emerged as a promising solution. However, applying deep learning for images processing is complex and often requires programming skills in Python, reducing its accessibility. Some authors addressed this issue with user-friendly software, and a further progress was the transposition of deep learning to R, a statistical language frequently used by ecologists, enhancing flexibility and customization of deep learning models without advanced computer expertise. We aimed to develop a user-friendly workflow based on R scripts to streamline the entire process, from selecting to classifying camera trap images. Our workflow integrates the MegaDetector object detector for labelling images and custom training of the state-of-the-art YOLOv8 model, together with potential for offline image augmentation to manage imbalanced datasets. Inference results are stored in a database compatible with Timelapse for quality checking of model predictions. We tested our workflow on images collected within a project targeting medium and large mammals of Central Italy, and obtained an overall precision of 0.962, a recall of 0.945, and a mean average precision of 0.913 for a training set of only 1000 pictures per species. Furthermore, the custom model achieved 91.8% of correct species-level classifications on a set of unclassified images, reaching 97.1% for those classified with > 90% confidence. YOLO, a fast and light deep learning architecture, enables application of the workflow even on resource-limited machines, and integration with image augmentation makes it useful even during early stages of data collection. All R scripts and pretrained models are available to enable adaptation of the workflow to other contexts, plus further development.

Design of the first full-scale HYLITE, a charge integration pixel detector readout chip for XFEL

HYLITE (High dYmamic range free electron Laser Imaging deTEctor) is a charge-integration detector readout chip designed for SHINE (Shanghai HIgh repetition rate XFEL aNd Extreme light facility), featuring a dynamic range of 10000 photons at 12 keV, a resolution of a single photon, and a high frame rate aiming for 10 kHz.HYLITE200F is the first full-scale chip of HYLITE manufactured in a 130 nm CMOS process. The engineering-run chip consists of 64 × 64 pixels with a pixel pitch of 200 μm. As the first step of the project, the HYLITE200F chip works at a frame rate of 1 kHz in a successive mode. To deal with the power supply issue and a high data rate, the layout of the pixel array and the clock distribution structure is carefully designed. Furthermore, prototype front-end modules were manufactured to verify the function of sensors, ASICs, and the reliability of the bump-bonding process. Test results show that HYLITE200F can work steadily at a frame rate of 1 kHz.

Prototype of Flexible Digital X-Ray Imaging Detector

Prototype of Flexible Digital X-Ray Imaging Detector