Pixel Detector Research Articles

Development of an associated particle imaging system with pixel SiC detectors

The elemental analysis method, with fast neutron associated particle imaging, holds immense potential in identifying concealed explosives, nuclear materials, and container security inspection, owing to its superior sensitivity and three-dimensional analysis capability compared to traditional neutron activation analysis technology. However, the temperature and irradiation fragility of the traditional associated particle detector curtails its usage in harsh environments such as space missions. The adoption of wide-bandgap semiconductor detectors, such as SiC, is expected to address this constraint. In this work, an associated particle imaging system based on a 4 × 4 SiC pixel detector was designed, built, and tested. The SiC detector exhibited consistent energy resolution and time performance between 25–150 °C. The built API system achieved an intrinsic time resolution of 1.8 ns and spatial resolution of at least 10 cm in the neutron flight direction. By utilizing the coincidence time spectrum and pixel SiC detector, the built system can provide the element content distribution in three-dimensional space. The results demonstrate the feasibility of employing SiC detectors in associated particle imaging systems and pave the way for developing a new type of sealed neutron tube with a prolonged lifetime and high environmental adaptability.

Volcanic Clouds Characterization of the 2020–2022 Sequence of Mt. Etna Lava Fountains Using MSG-SEVIRI and Products’ Cross-Comparison

From December 2020 to February 2022, 66 lava fountains (LF) occurred at Etna volcano (Italy). Despite their short duration (an average of about two hours), they produced a strong impact on human life, environment, and air traffic. In this work, the measurements collected from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument, on board Meteosat Second Generation (MSG) geostationary satellite, are processed every 15 min to characterize the volcanic clouds produced during the activities. In particular, a quantitative estimation of volcanic cloud top height (VCTH) and ash/ice/SO2 masses’ time series are obtained. VCTHs are computed by integrating three different retrieval approaches based on coldest pixel detection, plume tracking, and HYSPLIT models, while particles and gas retrievals are realized simultaneously by exploiting the Volcanic Plume Retrieval (VPR) real-time procedure. The discrimination between ashy and icy pixels is carried out by applying the Brightness Temperature Difference (BTD) method with thresholds obtained by making specific Radiative Transfer Model simulations. Results indicate a VCTH variation during the entire period between 4 and 13 km, while the SO2, ash, and ice total masses reach maximum values of about 50, 100, and 300 Gg, respectively. The cumulative ash, ice, and SO2 emitted from all the 2020–2022 LFs in the atmosphere are about 750, 2300, and 670 Gg, respectively. All the retrievals indicate that the overall activity can be grouped into 3 main periods in which it passes from high (December 2020 to March 2021), low (March to June 2021), and medium/high (June 2021 to February 2022). The different products have been validated by using TROPOspheric Monitoring Instrument (TROPOMI) polar satellite sensor, Volcano Observatory Notices for Aviation (VONA) bulletins, and by processing the SEVIRI data considering a different and more accurate retrieval approach. The products’ cross-comparison shows a generally good agreement, except for the SO2 total mass in case of high ash/ice content in the volcanic cloud.

Convolved Feature Vector Based Adaptive Fuzzy Filter for Image De-Noising

In this paper, a convolved feature vector based adaptive fuzzy filter is proposed for impulse noise removal. The proposed filter follows traditional approach, i.e., detection of noisy pixels based on certain criteria followed by filtering process. In the first step, proposed noise detection mechanism initially selects a small layer of input image pixels, convolves it with a set of weighted kernels to form a convolved feature vector layer. This layer of features is then passed to fuzzy inference system, where fuzzy membership degrees and reduced set of fuzzy rules play an important part to classify the pixel as noise-free, edge or noisy. Noise-free pixels in the filtering phase remain unaffected causing maximum detail preservation whereas noisy pixels are restored using fuzzy filter. This process is carried out traditionally starting from top left corner of the noisy image to the bottom right corner with a stride rate of one for small input layer and a stride rate of two during convolution. Convolved feature vector is very helpful in finding the edge information and hidden patterns in the input image that are affected by noise. The performance of the proposed study is tested on large data set using standard performance measures and the proposed technique outperforms many existing state of the art techniques with excellent detail preservation and effective noise removal capabilities.

PyTANSPEC: A data reduction package for TANSPEC

TIFR-ARIES Near Infrared Spectrometer (TANSPEC) instrument provides simultaneous wavelength coverage from 0.55 to 2.5 $$\mu $$ m, mounted on India’s largest ground-based telescope, 3.6-m Devasthal Optical Telescope at Nainital, India. The TANSPEC offers three modes of observations, imaging with various filters, spectroscopy in the low-resolution prism mode with derived $$R\sim 100$$ –400 and the high-resolution cross-dispersed mode (XD-mode) with derived median $$R\sim 2750$$ for a slit of width 0.5 arcsec. In the XD-mode, 10 cross-dispersed orders are packed in the $$2048 \times 2048$$ pixels detector to cover the full wavelength regime. As the XD-mode is most utilized as well as for consistent data reduction for all orders and to reduce data reduction time, a dedicated pipeline is essential. In this paper, we present the code for the TANSPEC XD-mode data reduction, its workflow, input/output files and a showcase of its implementation on a particular dataset. This publicly available pipeline pyTANSPEC is fully developed in Python and includes nominal human intervention only for the quality assurance of the reduced data. Two customized configuration files are used to guide the data reduction. The pipeline creates a log file for all the fit files in a given data directory from its header, identifies correct frames (science, continuum and calibration lamps) based upon the user input, offers an option to the user for eyeballing and accepting/removing of the frames, does the cleaning of raw science frames and yields final wavelength calibrated spectra of all orders simultaneously.

Equalizing the Pixel Response of the Imaging Photoelectric Polarimeter Onboard the IXPE Mission

The Gas Pixel Detector is a gas detector, sensitive to the polarization of X-rays, currently flying onboard the Imaging X-ray Polarimetry Explorer (IXPE)—the first observatory dedicated to X-ray polarimetry. It detects X-rays and their polarization by imaging the ionization tracks generated by photoelectrons absorbed in the sensitive volume, and then reconstructing the initial direction of the photoelectrons. The primary ionization charge is multiplied and ultimately collected on a finely pixellated ASIC specifically developed for X-ray polarimetry. The signal of individual pixels is processed independently and gain variations can be substantial, of the order of 20%. Such variations need to be equalized to correctly reconstruct the track shape, and therefore its polarization direction. The method to do such equalization is presented here and is based on the comparison between the mean charge of a pixel with respect to the other pixels for equivalent events. The method is shown to finely equalize the response of the detectors onboard IXPE, allowing a better track reconstruction and energy resolution, and can in principle be applied to any imaging detector based on tracks.

TOPAS-imaging: extensions to the TOPAS simulation toolkit for medical imaging systems

Objective. The TOol for PArticle Simulation (TOPAS) is a Geant4-based Monte Carlo software application that has been used for both research and clinical studies in medical physics. So far, most users of TOPAS have focused on radiotherapy-related studies, such as modeling radiation therapy delivery systems or patient dose calculation. Here, we present the first set of TOPAS extensions to make it easier for TOPAS users to model medical imaging systems. Approach. We used the extension system of TOPAS to implement pre-built, user-configurable geometry components such as detectors (e.g. flat-panel and multi-planar detectors) for various imaging modalities and pre-built, user-configurable scorers for medical imaging systems (e.g. digitizer chain). Main results. We developed a flexible set of extensions that can be adapted to solve research questions for a variety of imaging modalities. We then utilized these extensions to model specific examples of cone-beam CT (CBCT), positron emission tomography (PET), and prompt gamma (PG) systems. The first of these new geometry components, the FlatImager, was used to model example CBCT and PG systems. Detected signals were accumulated in each detector pixel to obtain the intensity of x-rays penetrating objects or prompt gammas from proton-nuclear interaction. The second of these new geometry components, the RingImager, was used to model an example PET system. Positron–electron annihilation signals were recorded in crystals of the RingImager and coincidences were detected. The simulated data were processed using corresponding post-processing algorithms for each modality and obtained results in good agreement with the expected true signals or experimental measurement. Significance. The newly developed extension is a first step to making it easier for TOPAS users to build and simulate medical imaging systems. Together with existing TOPAS tools, this extension can help integrate medical imaging systems with radiotherapy simulations for image-guided radiotherapy.

GEANT4 simulation and spectrum restoration of a pixelated X-ray detector

We perform a detailed simulation of a pixelated CdTe detector using the GEANT4 toolkit completed with a custom code emulating the detector's electronic response. We demonstrate that a measured tungsten X-ray spectrum can be majorly restored back to the original incident spectrum using the developed model, without requiring the dedicated hardware charge sharing correction.

The EXTRA-BL4S experiment for the measurement of the energy and angular distributions of transition radiation X-rays

We have designed and implemented an experiment to measure the angular distributions and the energy spectra of the transition radiation X-rays emitted by fast electrons and positrons crossing different radiators. Our experiment was selected among the proposals of the 2021 Beamline for Schools contest, a competition for high-school students organized every year by CERN, and was performed at the DESY II Test Beam facility area TB21, using a high-purity beam of electrons or positrons with momenta in the range from 1 to 6 GeV/c. The measurements were performed using a 100 μm thick silicon pixel detector, with a pitch of 55 μm. Our results are consistent with the expectations from the theoretical models describing the production of transition radiation in multilayer regular radiators.

Second generation Monitoring of Pixel System (MOPS) chip for the Detector Control System (DCS) of the ATLAS ITk Pixel detector

The MOPSv2 chip is an Application Specific Integrated Circuit (ASIC) to provide the temperature and the voltage monitoring data of individual front-end detector modules to the DCS of the ATLAS ITk Pixel detector. The chip implements CANopen in a hardwired logic, provides the possibility of remote reset without a power cycle and automated on-chip frequency trimming using CAN messages. The chip has proven to be radiation hard during testing up to an ionizing dose of 500 Mrad, immune to Single Event Upsets (SEUs) and works reliably under irradiation at high operating temperatures of up to 40 °C. In this paper, the functionality and performance of the second version of the chip will be discussed, and also results from the irradiation campaigns will be presented.

Development of novel low-mass module concepts based on MALTA monolithic pixel sensors

The MALTA CMOS monolithic silicon pixel sensors has been developed in the Tower 180 nm CMOS imaging process. It includes an asynchronous readout scheme and complies with the ATLAS inner tracker requirements for the HL-LHC. Several 4-chip MALTA modules have been built using Al wedge wire bonding to demonstrate the direct transfer of data from chip-to-chip and to read out the data of the entire module via one chip only. Novel technologies such as Anisotropic Conductive Films (ACF) and nanowires have been investigated to build a compact module. A lightweight flex with 17 μm trace spacing has been designed, allowing compact packaging with a direct attachment of the chip connection pads to the flex using these interconnection technologies. This contribution shows the current state of our work towards a flexible, low material, dense and reliable packaging and modularization of pixel detectors.

Prototype electronics for the silicon pad layers of the future Forward Calorimeter (FoCal) of the ALICE experiment at the LHC

A Forward Calorimeter (FoCal) has been proposed as part of the ALICE upgrades for data taking from 2029 onwards. The FoCal will feature a sampling electromagnetic calorimeter segmented into 110 towers supplemented by a hadron calorimeter. The electromagnetic calorimeter will be composed of 20 passive layers of tungsten absorber interleaved with 18 active layers of low-granularity silicon pad sensors and two layers of high-granularity pixel detectors. Each pad layer will be read out by 110 silicon pad sensors of 72 channels, amounting to a total of 1980 sensors.This paper describes, from front-end to back-end, the electronics developed to instrument a towerprototype composed of 18 silicon pad sensors as well as a design proposal for the full-detectorreadout system.

Polarisation leakage due to errors in track reconstruction in gas pixel detectors

X-ray polarimetry based on gas pixel detectors (GPDs) has reached a high level of maturity thanks to the Imaging X-ray Polarimeter Explorer (IXPE) providing the first-ever spatially resolved polarimetric measurements. However, as this a new technique, a few unexpected effects have emerged in the course of in-flight operations. In particular, it was almost immediately found that, the unpolarized calibration sources on-board were showing radially polarized halos. The origin of these features was recognized in a correlation between the error in reconstructing the absorption point of the X-ray photon and the direction of its electric field vector. Here, we present and discuss this effect in detail, showing that it is possible to provide a simple and robust mathematical formalism to handle it. We further show its role and relevance for the recent IXPE measures as well as for the use of GPD-based techniques in general. We also illustrate how to model it in the context of studying extended sources.

Phase ambiguity resolution and mixed pixel detection in EDM with multiple modulation wavelengths

Distance measurement based on the accumulated phase of intensity-modulated continuous-wave lasers is an established approach for pointwise geometry acquisition in uncontrolled conditions, enabling some of the most accurate Lidar/laser-scanning solutions. Inherently affected by cycle ambiguities due to the modulo 2π phase observations, several modulation wavelengths are typically used in practical implementations to extend the measurement range. One of the main limitations of these systems arises from their inability to decouple mixed signals affected by different delays. This is especially relevant when the laser beam illuminates simultaneously two or more surfaces at significantly different distances, producing mixed-pixel measurements in which the estimated distance does not reliably correspond to any of the involved scatterers. Algorithms for detection and filtering of mixed pixels within point-cloud data have been proposed based on analyzing consistency across local neighborhoods. The resolution of multiple scatterers on individual measurements, however, has not been yet reported nor is provided by undisclosed commercial implementations. In this work, we analyze the problem of signal mixing in multi-wavelength phase-based distance estimation, and propose an algorithm for joint phase ambiguity resolution and mixed pixel detection based on mixed integer linear programming. We first analyze theoretically the performance limits of the proposed solution, demonstrating unbiasedness in the presence of noise and robustness in the presence of multiple scatterers. In addition, we investigate empirically the impact of noise, mixed measurements and choice of modulation wavelengths on the performance of the proposed algorithm. The results demonstrate the capacity of the presented approach, given an adequate wavelength selection, to provide unambiguous distance estimates under realistic noise conditions and to identify measurements affected by mixed pixels while approximating the position of the dominant scatterer. Aside from contributing to improving the reliability and resolution capability of Lidar and laser-scanning data, the proposed solution sets a promising step towards fully resolved multi-target distance measurement.

A novel concept of adjustable three-layer collimator in a pixelated photon-counting detector for gamma-ray imaging: Monte Carlo simulation study

In gamma-ray imaging, a collimator plays a crucial role in determining the sensitivity of the system and the spatial resolution of the acquired image. Herein, we presented a novel concept for a variable collimator in a pixelated photon-counting detector. The gamma-ray imaging system was modeled using the Monte Carlo simulation tool Geant4 Application for Tomographic Emission program. A detector using cadmium telluride and a 99mTc point source was used. The collimators comprised three tungsten layers, and the septal height the beam finally penetrated from the incident gamma ray was adjusted differently. The first collimator layer constituted a hole with four times the pixel size, and the second and third layers comprised a hole with twice the pixel size, overlapping asymmetrically. Finally, the emitted gamma ray equaled the pixel. The spatial resolution showed different results depending on the source-to-collimator distance for each collimator configuration. Additionally, we determined that the sensitivity improved as the collimator height where gamma rays are incident and initially interact increased. We have proposed a novel collimator concept in a gamma-ray imaging system using a pixelated photon-counting detector, which may be applied in various fields in the future.

Correction of ring artifacts with Swin-Conv-U-Net for x-ray computed tomography

X-ray tomography is widely used in diverse research domains owing to its capacity for observing high-resolution three-dimensional structures nondestructively. However, ring artifacts appear in the tomographic reconstruction because of the inconsistent response of detector pixels, seriously affecting the image quality and causing nonuniform bias. To solve this problem, a method for correction of ring artifacts based on Swin-Conv-U-Net is proposed for x-ray tomography. When applied to simulation and experimental data, the proposed method achieves high accuracy and strong robustness and shows advantages over several classical methods in quantitative and qualitative evaluation.

Methodology for measuring the fill factor of silicon photomultipliers

The fill factor (FF) is an important parameter and widely used in pixelated detectors, such as Silicon Photomultipliers (SiPMs), pixelated imagers, pixelated radiation detectors. FF is the ratio of photosensitive area to the total detector area. For the SiPMs, FF plays an important role in the photon detection efficiency (PDE). However, relatively few reports have focused on measuring the FF of SiPMs. This article describes a method to optically measure the effective FF of SiPMs based on our proposed criterion formula and the two-dimensional micro-spatial distribution of the avalanche pulse count rate of SiPM. The FFs of five different SiPMs were measured and analyzed using the developed method. Experimental results confirm that the effective FFs of SiPMs can be conveniently evaluated using the method proposed herein, which can provide reference for optimizing the design and manufacture of SiPMs. This method is also applicable for FF measurements involving other photon sensors.

Deep-learning-based ring artifact correction for tomographic reconstruction.

X-ray tomography has been widely used in various research fields thanks to its capability of observing 3D structures with high resolution non-destructively. However, due to the nonlinearity and inconsistency of detector pixels, ring artifacts usually appear in tomographic reconstruction, which may compromise image quality and cause nonuniform bias. This study proposes a new ring artifact correction method based on the residual neural network (ResNet) for X-ray tomography. The artifact correction network uses complementary information of each wavelet coefficient and a residual mechanism of the residual block to obtain high-precision artifacts through low operation costs. In addition, a regularization term is used to accurately extract stripe artifacts in sinograms, so that the network can better preserve image details while accurately separating artifacts. When applied to simulation and experimental data, the proposed method shows a good suppression of ring artifacts. To solve the problem of insufficient training data, ResNet is trained through the transfer learning strategy, which brings advantages of robustness, versatility and low computing cost.

Mobile visual media design based on artificial intelligence and augmented reality technology

Abstract In recent years, with the development of computer and network technologies, digital video and image information is emerging more and more, the information era based on multimedia information services is coming to us, and people’s demand for visual media content such as video and images is becoming more and more extensive. In this paper, we use the Gaussian mixture model pixel detection technology method and image detection technology to study visual media to meet the various needs of users. SVM is used to perform classification tests on 3688 Chinese painting images and 4827 general images. The result is that the positive detection rate of national painting images is 87.25%, and the rate of non-national painting images being wrongly detected as national painting images is 7.63%. This indicates that the CCV feature also has a relatively good discriminative property for national painting images. The focus is on providing technical methods for the design of various visual media shapes such as sports and art, thus providing solutions to help users better access and use the digital multimedia information they are interested in.

Compressed phase coding-based optical image encryption

With the development of artificial intelligence technology, the traditional inflexible optical image encryption system has been difficult to resist security attacks such as chosen-plaintext attack and known-plaintext attack, and its security has been greatly challenged. Therefore, an optical image encryption method based on compressed phase coding is proposed, in which a spatial light modulator (SLM) is used to encode the phase of the optical system randomly, and then combined with the measurement matrix in the single pixel sampling process to build a flexible key system. In the encryption process, a phase-only SLM is firstly implemented to realize phase encoding of the original plaintext image and loading the phase key. Then the modulated reference light is implemented to further hide the complex amplitude distribution of the encrypted image. Finally, the encoded object light and reference light are coherently superimposed in the digital micromirror device (DMD), and the inner product operation is carried out with the measurement matrix to realize further encryption and collected by the single pixel detector. Both simulation and experiment proved that the proposed compressed phase coding-based image encryption system is similar to "one time one pad" cryptographic system, which greatly improves the security of the optical encryption system.

Handling the Background in IXPE Polarimetric Data

Imaging X-ray Polarimetry Explorer (IXPE) is a Small Explorer mission by NASA and Agenzia Spaziale Italiana, launched on 2021 December 9, dedicated to investigating X-ray polarimetry allowing angular-, time-, and energy-resolved observations in the 2–8 keV energy band. IXPE is in the science observation phase since 2022 January; it is comprised of three identical telescopes with grazing-incidence mirrors, each one having in the focal plane a gas pixel detector. In this paper, we present a possible guideline to obtain an optimal background selection in polarimetric analysis, and a rejection strategy to remove instrumental background. This work is based on the analysis of IXPE observations, aiming to improve as much as possible the polarimetric sensitivity. In particular, the developed strategies have been applied as a case study to the IXPE observation of the 4U 0142+61 magnetar.