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Uncooled and shutterless microbolometer cameras are good candidates for infrared imaging systems installed on small satellites or small unmanned aerial vehicles: they are light and passive since no cooling system or mechanical shutter is required and they can be operated at ambient temperatures. However, the radiometric compensation has to be carefully performed to make the system compatible with applications where the radiometric accuracy of the images is mandatory. In this paper, we study the impact of the camera environment to the radiometric accuracy of the images. We propose and test hardware and software solutions to improve this accuracy and the quality of the radiometric images. We show that the radiometric calibration of the camera with our model is valid over a long time period— about 3 years—using in-door experiments. [ABSTRACT FROM AUTHOR]

The growing interests have been witnessed in the evolution and improvement of artificial compound eyes (CE) inspired by arthropods. However, the existing CE cameras are suffering from a defocusing problem due to the incompatibility with commercial CMOS cameras. Inspired by the CEs of South American Shrimps, we report a compact biologically inspired camera that enables wide-field-of-view (FOV), high-resolution imaging and sensitive 3D moving trajectory reconstruction. To overcome the defocusing problem, a deep learning architecture with distance regulation is proposed to achieve wide-range-clear imaging, without any hardware or complex front-end design, which greatly reduces system complexity and size. The architecture is composed of a variant of Unet and Pyramid-multi-scale attention, with designed short, middle and long distance regulation. Compared to the current competitive well-known models, our method is at least 2 dB ahead. Here we describe the high-resolution computational-CE camera with 271 ommatidia, with a weight of 5.4 g an area of 3 × 3 cm2 and 5-mm thickness, which achieves compatibility and integration of CE with commercial CMOS. The experimental result illustrates this computational-CE camera has competitive advantages in enhanced resolution and sensitive 3D live moving trajectory reconstruction. The compact camera has promising applications in nano-optics fields such as medical endoscopy, panoramic imaging and vision robotics. [ABSTRACT FROM AUTHOR]

In this paper, a low-cost, Raspberry Pi based imaging system is proposed as compact standalone interrogation unit for analysis of fiber specklegram sensors. Standard methods for specklegram analysis are based on image correlation. Proposed imaging system is used for both capturing specklegram images at the output of the standard telecommunication optical fiber and for correlation analysis. Experimental setup for controlled mechanical deformation of the optical fiber is designed and zero-normalized cross-correlation, structural similarity and normalized mutual information score correlation methods are implemented and compared in order to verify proposed Raspberry Pi based imaging system functionally. A statistical method for detection of region of interest is used for dynamic output range extension. Additionally, to further extend dynamic range and increase linearity, correlation output is provided as difference of correlation coefficient for two reference samples located at the ends of measurement range. [ABSTRACT FROM AUTHOR]

For the purpose of achieving long-range, high-resolution, and ultra-wide-swath airborne earth imaging at extremely low-light levels (0.01 Lux), a low-light imaging system built on multi-detector optical butting was researched. Having decomposed the system's specifications and verified its low-light imaging capability, we proposed to employ an optical system with a large relative aperture and low distortion and achieve imaging through the field-of-view (FOV) butting facilitated by eight 1080P high-sensitivity scientific complementary metal-oxide semiconductor (SCMOS) detectors. This paper elaborates on the design concept of the mechanical configuration of the imaging system; studies the calculation method of the structural parameters of the reflection prism; provides mathematical expressions for geometric parameters, such as the length and width of the splicing prism; and designs in detail the splicing structure of six reflection prisms for eight-channel beam splitting. Based on the design and computational results, a high-resolution, wide-swath imaging system for an ambient illuminance of 0.01 Lux was developed. Exhibiting a ground sampling distance (GSD) of 0.5 m (at a flight height of 5 km), this low-light imaging system keeps the FOV overlap ratio between adjacent detectors below 3% and boasts an effective image resolution of 4222 × 3782. The results from flight testing revealed that the proposed imaging system is capable of generating wide-swath, high-contrast resolution imagery under airborne and low-light conditions. As such, the way the system is prepared can serve as a reference point for the development of airborne low-light imaging devices. [ABSTRACT FROM AUTHOR]

Tilt-to-length (TTL) coupling noise arises from angular misalignments of interfering beams in optical path length (OPL) measurements and significantly impacts the accuracy of interferometry measurement systems. This paper focuses on geometric TTL coupling in a test mass (TM) interferometer and examines how an imaging system influences TTL noise suppression. First, the analytical expression of the geometric TTL coupling in a TM interferometer with alignment errors is derived and confirmed through numerical simulation. Subsequently, an imaging system is incorporated into the geometric model and the corresponding analytical expressions are obtained under two common conjugate relationships. Nevertheless, the TTL coupling remains beyond the requirement of TM interferometer, as the residual TTL coupled with alignment errors persists even with the imaging system. Therefore, an optimal position of the imaging system capable of eliminating the second-order term of the TTL coupling is determined. Meanwhile, the first-order term can be mitigated through in-orbit calibrations. These findings offer valuable guidance for the design and adjustment of imaging systems in space-borne gravitational wave detection missions, which require high-precision laser interferometry. [ABSTRACT FROM AUTHOR]

Accurate in-vivo verification of beam range and dose distribution is crucial for the safety and effectiveness of particle therapy. Prompt gamma (PG) imaging, as a method for real-time verification, has gained prominence in this area. Currently, several PG imaging systems are under development, including gamma electron vertex imaging (GEVI), the Compton camera, the slit camera, and the multi-array type collimator camera. However, challenges persist in dose prediction accuracy, largely due to patient positioning uncertainty and anatomical changes. Although each system demonstrates potential in verifying PG range, further improvements in detection efficiency, spatial resolution, background reduction, and integration into clinical workflows are essential. [ABSTRACT FROM AUTHOR]

In this paper, based on a simplified dermis model of cylinder-birefringence, the variation of polarization properties of human skin with its structural parameters was studied. To the best of our knowledge, for the first time, the birefringence parameters of human skin measured by polarization-sensitive optical coherence tomography system was used to analyze the changes of birefringence, dichroism and depolarization with the change of structural parameters. The results of this study are important for interpreting the results of polarization experiments, diagnosing human skin diseases and monitoring the effects of treatment in vivo. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Data Acquisition & Processing / Shu Ju Cai Ji Yu Chu Li is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A low frequency wavefront aberration correction method for solar telescopes based on secondary mirror movement is proposed to correct dynamic wavefront aberration during the operation of solar telescope. The correction ability of this method is analyzed and validated by numerical simulation and experiments. Theoretical analysis and numerical simulation both indicate the system processes significant aberration correction ability given the correction frequency of the secondary mirror movement is 10 times higher than aberration frequency. After spatiotemporal frequency division of actual wavefront data from solar telescope, the experiment result proves that the proposed correction method based on secondary mirror movement can effectively reduce the overall RMS of dynamic aberrations with high-frequency portion.

Systems neuroscience is focused on how ensemble properties in the brain, such as the activity of neuronal circuits, gives rise to internal brain states and behavior. Many of the studies in this field have traditionally involved electrophysiological recordings and computational approaches that attempt to decode how the brain transforms inputs into functional outputs. More recently, systems neuroscience has received an infusion of approaches and techniques that allow the manipulation (e.g., optogenetics, chemogenetics) and imaging (e.g., two-photon imaging, head mounted fluorescent microscopes) of neurons, neurocircuits, their inputs and outputs. Here, we will review novel approaches that allow the manipulation and imaging of specific molecular mechanisms in specific cells (not just neurons), cell ensembles and brain regions. These molecular approaches, with the specificity and temporal resolution appropriate for systems studies, promise to infuse the field with novel ideas, emphases and directions, and are motivating the emergence of a molecularly oriented systems neuroscience, a new discipline that studies how the spatial and temporal patterns of molecular systems modulate circuits and brain networks, and consequently shape the properties of brain states and behavior.

We discuss a problem of reconstructing (sectioning) multilayer object images in observed images obtained by focusing the imaging system on each layer and containing spurious blurry images of neighboring layers. The blurring model used describes a physical process of incoherent light scattering in the Fresnel approximation with a priori unknown parameters of the point spread function. We propose a method of "Boundary separation" of sectioning, which combines the use of a physical blur model with modern methods of blur estimating and edge detection. The results of testing the "Boundary separation" method on the data of physical experiments with different-scale model multilayer objects are analyzed and compared with the existing methods for solving the optical sectioning problem. It is concluded that the method is most effective on multilayer objects with clearly defined boundaries, on which the method has demonstrated almost complete restoration of the desired layers.

Abstract Purpose The aim of this study was to evaluate and summarize the developmental rules of the ocular anterior segment of neonates by means of wild-field digital imaging system. Methods We used the wide-field digital imaging system to sequentially capture images of the neonates’ eyes within 42 days after delivery, including the ocular surface, anterior segment, and fundus. At the same time, basic information at the time of birth and examination was collected. Results Among 248 newborns, 51.21% were male. Abnormalities of the anterior segment such as visualization of anterior chamber angle vessels (79.03%) and iris vessels (51.21%), iris process (42.34%), persistent pupillary membranes (19.35%), albinism, congenital cataracts, corneal leucoma, and subconjunctival hemorrhage were observed in this study. There were significant differences in the appearance of iris vessels among different sex, gestational age and birth weight, postmenstrual age and weight at the time of examination and iris color groups. The iris vessels were more visualized in males relative to females (OR = 6.313, 95% CI 2.529–15.759). The greater the postmenstrual age at the time of examination, the lower the visualization of iris vessels (OR = 0.377, 95% CI 0.247–0.575). In addition, although visualization of anterior chamber angle vessels differed within the birth gestation age and weight at examination groups, there was no significant correlation by regression analysis. Conclusions The anterior segment of perinatal neonates can be visualized by the wide-field digital imaging system. The neonatal iris and anterior chamber angle are immature, and the visible vessels at the anterior chamber angle that vanish later than the surface of the iris are characteristic structures.

Accurate in-vivo verification of beam range and dose distribution is crucial for the safety and effectiveness of particle therapy. Prompt gamma (PG) imaging, as a method for real-time verification, has gained prominence in this area. Currently, several PG imaging systems are under development, including gamma electron vertex imaging (GEVI), the Compton camera, the slit camera, and the multi-array type collimator camera. However, challenges persist in dose prediction accuracy, largely due to patient positioning uncertainty and anatomical changes. Although each system demonstrates potential in verifying PG range, further improvements in detection efficiency, spatial resolution, background reduction, and integration into clinical workflows are essential.

Defence Science and Technology Group (DSTG) is currently preparing for the launch of the Buccaneer Main Mission (BMM) satellite, the successor to the Buccaneer Risk Mitigation Mission (BRMM). BMM hosts a high-frequency (HF) antenna and receiver to contribute to the calibration of the Jindalee Operational Radar Network (JORN). Verification of the successful deployment and stability of the large HF antenna is critical to the success of the mission. A bespoke deployable optics payload has been developed by DSTG to fulfil the dual purpose of direct verification of the deployed state of the HF antenna and capturing images of the Earth through a rotatable, dual-surfaced mirror and a variable-focus liquid lens. The payload advances research at DSTG in several fields of space engineering, including deployable mechanisms, precision actuation devices, radiation-tolerant electronics, advanced metal polishing and optical metrology. This paper discusses the payload design, material selection, trade-offs considered for the deployable optics payload and preliminary test results. [ABSTRACT FROM AUTHOR]

Abstract High performance imaging in parallel cameras is a worldwide challenge in computational optics studies. However, the existing solutions are suffering from a fundamental contradiction between the field of view (FOV), resolution and bandwidth, in which system speed and FOV decrease as system scale increases. Inspired by the compound eyes of mantis shrimp and zoom cameras, here we break these bottlenecks by proposing a deep learning-based parallel (DLBP) camera, with an 8-μrad instantaneous FOV and 4 × computational zoom at 30 frames per second. Using the DLBP camera, the snapshot of 30-MPs images is captured at 30 fps, leading to orders-of-magnitude reductions in system complexity and costs. Instead of directly capturing photography with large scale, our interactive-zoom platform operates to enhance resolution using deep learning. The proposed end-to-end model mainly consists of multiple convolution layers, attention layers and deconvolution layer, which preserves more detailed information that the image reconstructs in real time compared with the famous super-resolution methods, and it can be applied to any similar system without any modification. Benefiting from computational zoom without any additional drive and optical component, the DLBP camera provides unprecedented-competitive advantages in improving zoom response time (~ 100 ×) over the comparison systems. Herein, with the experimental system described in this work, the DLBP camera provides a novel strategy to solve the inherent contradiction among FOV, resolution and bandwidth.

Palmprint has been widely used in biometric systems because of its durability and reliability. To avoid recognition performance degradation, dynamic region of interest extraction is a critical step for these systems. In this study, a low-cost contactless palmprint imaging system has been designed and a dynamic region of interest extraction method has been applied to palmprints using the MediaPipe Hands framework. Since the need for hygienic touchless systems has been realized in the post-COVID-19 pandemic world, a low-cost imaging system has been proposed to capture the user’s hand at a distance without touching any platform. The region of interest of the user's palmprints in a real-time video stream has been extracted dynamically. This study creates a paradigm for future studies on palmprint imaging. With conducted experiments, the potential of MediaPipe Hands in terms of speed and accuracy on mobile palmprint imaging applications has been realized on Raspberry Pi 4. This work demonstrates that the employed hardware and proposed hand-tracking algorithm are suitable for designing low-cost contactless palmprint imaging systems in non-controlled ambient light conditions. For recognition purposes, a database will be released soon.

For the purpose of achieving long-range, high-resolution, and ultra-wide-swath airborne earth imaging at extremely low-light levels (0.01 Lux), a low-light imaging system built on multi-detector optical butting was researched. Having decomposed the system’s specifications and verified its low-light imaging capability, we proposed to employ an optical system with a large relative aperture and low distortion and achieve imaging through the field-of-view (FOV) butting facilitated by eight 1080P high-sensitivity scientific complementary metal-oxide semiconductor (SCMOS) detectors. This paper elaborates on the design concept of the mechanical configuration of the imaging system; studies the calculation method of the structural parameters of the reflection prism; provides mathematical expressions for geometric parameters, such as the length and width of the splicing prism; and designs in detail the splicing structure of six reflection prisms for eight-channel beam splitting. Based on the design and computational results, a high-resolution, wide-swath imaging system for an ambient illuminance of 0.01 Lux was developed. Exhibiting a ground sampling distance (GSD) of 0.5 m (at a flight height of 5 km), this low-light imaging system keeps the FOV overlap ratio between adjacent detectors below 3% and boasts an effective image resolution of 4222 × 3782. The results from flight testing revealed that the proposed imaging system is capable of generating wide-swath, high-contrast resolution imagery under airborne and low-light conditions. As such, the way the system is prepared can serve as a reference point for the development of airborne low-light imaging devices.

Tilt-to-length (TTL) coupling noise arises from angular misalignments of interfering beams in optical path length (OPL) measurements and significantly impacts the accuracy of interferometry measurement systems. This paper focuses on geometric TTL coupling in a test mass (TM) interferometer and examines how an imaging system influences TTL noise suppression. First, the analytical expression of the geometric TTL coupling in a TM interferometer with alignment errors is derived and confirmed through numerical simulation. Subsequently, an imaging system is incorporated into the geometric model and the corresponding analytical expressions are obtained under two common conjugate relationships. Nevertheless, the TTL coupling remains beyond the requirement of TM interferometer, as the residual TTL coupled with alignment errors persists even with the imaging system. Therefore, an optimal position of the imaging system capable of eliminating the second-order term of the TTL coupling is determined. Meanwhile, the first-order term can be mitigated through in-orbit calibrations. These findings offer valuable guidance for the design and adjustment of imaging systems in space-borne gravitational wave detection missions, which require high-precision laser interferometry.

Purpose: The aim of this study was to evaluate and summarize the developmental rules of the ocular anterior segment of neonates by means of wild-field digital imaging system. Methods: We used the wide-field digital imaging system to sequentially capture images of the neonates' eyes within 42 days after delivery, including the ocular surface, anterior segment, and fundus. At the same time, basic information at the time of birth and examination was collected. Results: Among 248 newborns, 51.21% were male. Abnormalities of the anterior segment such as visualization of anterior chamber angle vessels (79.03%) and iris vessels (51.21%), iris process (42.34%), persistent pupillary membranes (19.35%), albinism, congenital cataracts, corneal leucoma, and subconjunctival hemorrhage were observed in this study. There were significant differences in the appearance of iris vessels among different sex, gestational age and birth weight, postmenstrual age and weight at the time of examination and iris color groups. The iris vessels were more visualized in males relative to females (OR = 6.313, 95% CI 2.529–15.759). The greater the postmenstrual age at the time of examination, the lower the visualization of iris vessels (OR = 0.377, 95% CI 0.247–0.575). In addition, although visualization of anterior chamber angle vessels differed within the birth gestation age and weight at examination groups, there was no significant correlation by regression analysis. Conclusions: The anterior segment of perinatal neonates can be visualized by the wide-field digital imaging system. The neonatal iris and anterior chamber angle are immature, and the visible vessels at the anterior chamber angle that vanish later than the surface of the iris are characteristic structures. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Noise is a significant factor affecting imaging quality because it seriously reduces the detection signal-to-noise ratio (SNR), especially in feeble-light detection. In this paper, we propose a practical method to separate signal from noise background in ghost imaging (GI) systems based on correlation calculation. Experiments have shown that this method can significantly increase the SNR of the reconstructed images. Our research provides a novel method for suppressing noise influence on feeble-light GI, which has valuable reference value in biomedicine and remote sensing.

The near-space atmosphere is thin, and the atmospheric refraction and scattering on optical observation is very small, making it very suitable for wide-area and high-resolution surveillance using high-altitude balloon platforms. This paper adopts a 9344 × 7000 CMOS sensor to obtain high-resolution images, generating large-field-of-view imaging through the swing scanning of the photoelectric sphere and image stitching. In addition, a zoom lens is designed to achieve flexible applications for different scenarios, such as large-field-of-view and high-resolution imaging. The optical design results show that the camera system has good imaging quality within the focal length range of 320 mm–106.7 mm, and the relative distortion values at different focal lengths are less than 2%. The flight results indicate that the system can achieve seamless image stitching at a resolution of 0.2 m@20 km and the imaging field of view angle exceeds 33°. This system will perform other near-space flight experiments to verify its ultra-wide (field of view exceeding 100°) high-resolution imaging application. [ABSTRACT FROM AUTHOR]

Abnormal changes of the nasolabial sulcus characteristics are important symptoms of stroke, usually as the basis for the stroke facial diagnosis by traditional Chinese medicine with naked-eye observation. In order to quantify the characteristics of nasolabial sulcus and to solve the problem that it is difficult to find fine feature changes and difficult to communicate information in traditional Chinese medicine facial diagnosis, the polarization parametric indirect macroscopic imaging (PIMI) method was adopted by using the Stokes St parametric image. The nasolabial sulcus characteristics of healthy people, stroke patients, and prognostic people were obtained. The results show that the nasolabial sulcus St data of healthy people has good symmetry, while it is obviously asymmetrical for the stroke patients, and the difference between the left and right peaks is more than 20. It becomes more symmetrical when the stroke patient gets better. This method is expected to be applied to the digital diagnosis of stroke diseases and the evaluation of the treatment process, promoting the development of digital Chinese medicine. [ABSTRACT FROM AUTHOR]

The sCMOS imaging system with deep vacuum cooling technology has become a necessary way to improve the detection capability of space targets. In order to improve the detection capability of the photoelectric detection equipment for space targets, this paper developed the Highly Sensitive Deep Vacuum Cooling Imaging System (HSDVCIS). Firstly, we designed the imaging readout processing circuit using the GSENSE4040 sCMOS image sensor designed and manufactured by Gpixel and the deep vacuum cooling structure using thermoelectric cooling. Then, we tested the designed HSDVCIS with readout noise, dark current, and dynamic range of 3.96 e − , 0.12 e − /pixel/sec, and 84.49 dB, respectively, and tested the image sensor with a minimum cooling temperature of −40 °C. Finally, according to the results of observation experiments, we validated that the photoelectric detection equipment equipped with HSDVCIS improved the limiting detection magnitude (at SNR = 5 level) from 13.22 to 13.51 magnitudes within a 3 s exposure time by turning on the cooling function. Therefore, HSDVCIS designed in this paper can achieve highly sensitive detection of space targets. At the same time, the development of HSDVCIS also provides technical reserves and strong support for future research on the imaging systems using multiple image sensor mosaics. [ABSTRACT FROM AUTHOR]

High performance imaging in parallel cameras is a worldwide challenge in computational optics studies. However, the existing solutions are suffering from a fundamental contradiction between the field of view (FOV), resolution and bandwidth, in which system speed and FOV decrease as system scale increases. Inspired by the compound eyes of mantis shrimp and zoom cameras, here we break these bottlenecks by proposing a deep learning-based parallel (DLBP) camera, with an 8-μrad instantaneous FOV and 4 × computational zoom at 30 frames per second. Using the DLBP camera, the snapshot of 30-MPs images is captured at 30 fps, leading to orders-of-magnitude reductions in system complexity and costs. Instead of directly capturing photography with large scale, our interactive-zoom platform operates to enhance resolution using deep learning. The proposed end-to-end model mainly consists of multiple convolution layers, attention layers and deconvolution layer, which preserves more detailed information that the image reconstructs in real time compared with the famous super-resolution methods, and it can be applied to any similar system without any modification. Benefiting from computational zoom without any additional drive and optical component, the DLBP camera provides unprecedented-competitive advantages in improving zoom response time (~ 100 ×) over the comparison systems. Herein, with the experimental system described in this work, the DLBP camera provides a novel strategy to solve the inherent contradiction among FOV, resolution and bandwidth. [ABSTRACT FROM AUTHOR]

Metasurfaces can modulate light with periodically arranged subwavelength scatterers, and they can generate arbitrary wavefronts. Therefore, they can be used to realize various optical components. In particular, metasurfaces can be used to realize lenses, so-called metalenses. In the last decade, metalenses have been actively studied and developed. In this review, we firstly introduce the fundamental principles of metalenses in terms of materials, phase modulation method, and design method. Based on these principles, the functionalities and the applications can consequently be realized. Metalenses have a much larger number of degrees of freedom compared with that of existing refractive or diffractive lenses. Thus, they afford functionalities such as tunability, high numerical aperture, and aberration correction. Metalenses with these functionalities can be applied in various optical systems such as imaging systems and spectrometers. Finally, we discuss the future applications of metalenses. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a broadband superheterodyne receiver (RX) front‐end for millimeter‐wave (mm‐Wave) imaging radar is presented. Realized in 28‐nm CMOS technology, the proposed RX incorporates a wideband low‐noise amplifier (LNA), double‐balanced passive mixers for the dual down‐conversion, a differential power divider, a differential intermediate frequency filters, a current‐mode‐logic divider‐by‐2, and a local oscillator buffers. Wideband technique and layout optimization are taken into consideration in the RX. A four‐stage LNA is devised to realize the high gain and low noise figure (NF) with a common‐gate input stage and three pseudodifferential common‐source stages. Optimized transistor layout and capacitor neutralization technique are developed to improve gain and noise performance. Transformer‐based matching networks with the peak‐staggered technique are adopted in the LNA to achieve a flatter gain response with a wider bandwidth (BW). The passive double‐balanced mixers are implemented with a highly symmetrical layout for broadband down‐conversion. Simulation results show that the mm‐Wave RX front‐end exhibits a BW ranging from 90 to 115 GHz. The simulated NF of our RX is 4.7 dB at 86 GHz. With a supply voltage of 1 V, the presented RX consumes 88.2‐mW power and occupies a chip size of 1.6 × 0.5 mm2 including all the testing pads. The proposed RX is suitable for W‐band imaging systems. [ABSTRACT FROM AUTHOR]

With the growing importance of single-photon-counting (SPC) techniques, researchers are now designing high-performance systems based on single-photon avalanche diodes (SPADs). SPADs with high performances and low cost allow the popularity of SPC-based systems for medical and industrial applications. However, few efforts were put into the design optimization of SPADs due to limited calibrated models of the SPAD itself and its related circuits. This paper provides a perspective on improving SPAD-based system design by reviewing the development of SPAD models. First, important SPAD principles such as photon detection probability (PDP), dark count rate (DCR), afterpulsing probability (AP), and timing jitter (TJ) are discussed. Then a comprehensive discussion of various SPAD models focusing on each of the parameters is provided. Finally, important research challenges regarding the development of more advanced SPAD models are summarized, followed by the outlook for the future development of SPAD models and emerging SPAD modeling methods. [ABSTRACT FROM AUTHOR]

Hadamard single-pixel imaging (SPI) employs the differential measurement strategy to eliminate the effect of negative value of Hadamard basis patterns but leads to doubling the number of measurements. To reduce the number of measurements, a Hadamard SPI method based on positive patterns is proposed. In this method, only the positive patterns are used to acquire measurement values and reconstruct images, so the number of measurements will be reduced by 1/2. Combined with the intensity correlation theory of ghost imaging, the average value of the acquired measures is found; this average value is subtracted from all the measurement values to obtain the spectral coefficients, thus the background noise is eliminated to ensure the imaging quality. Simulation and experimental results show that the proposed method has good noise robustness and can efficiently reconstruct high quality images. [ABSTRACT FROM AUTHOR]

Abstract Background The production of a good quality chest radiograph depends on the selection of appropriate kilovoltage and current–time product while keeping the radiation dose to patients as low as possible. This study assessed radiographers’ level of compliance to the use of high kV as standard for postero-anterior (PA) chest X-ray in the South South region of Nigeria. Results Seventy-seven of the 82 questionnaires administered were completely filled and returned giving a response rate of 94%. Of these 77 respondents, only 74% (n = 57) were aware of high-kV technique as the recommended procedure for PA chest X-ray. Departmental protocols (technique chart with exposure factors) were also non-existent in all hospitals/diagnostic centres used in this study. Thirty-one respondents were males (40%); 44% (n = 34) working in public hospitals only and 32% (n = 25) with less than five years of working experience were aware of this technique. On the benefits, more than 50% of the respondents were familiar with the benefits of using high-kV technique as the recommended standard for PA chest X-rays. Responses on the benefits of the technique varied from 77% (n = 59) for patient dose reduction to 51% (n = 39) for better imaging of the airways. The use of high-kV technique for PA chest X-rays showed only 13% compliance. Factors influencing compliance included imaging system (film screen /digital), X-ray tube rating and X-ray unit with preset/manual exposure factors (p

The article considers the problem of finding the blur parameter between two images for the optical sectioning problem, in which the blur model has a natural optical origin associated with the use of incoherent white light as a radiation source in the Fresnel approximation. A method for solving this problem is proposed, and a general scheme for finding the blur coefficient for the point spread function based on a comparison of the gradients of the original and blurred images is described. Image gradients are calculated through partial derivatives of the Gaussian function, which makes it possible to smooth out possible background noise in images. The article presents the results of testing the method on simulated and real images with different noise levels. The results show that the developed method well detects the desired parameters in noisy images, and the detection error does not exceed the noise level, and for images without noise, the method accurately finds the desired parameters. An important design feature of the method is the ability to replace one type of point scattering function with another, which allows adapting the algorithm to other problems in which the image is formed on the basis of the convolution of the object with the point scattering function.

Fluorescence-guided surgery (FGS) and other interventions are rapidly evolving as a class of technologically driven interventional approaches in which many surgical specialties visualize fluorescent molecular tracers or biomarkers through associated cameras or oculars to guide clinical decisions on pathological lesion detection and excision/ablation. The technology has been commercialized for some specific applications, but also presents technical challenges unique to optical imaging that could confound the utility of some interventional procedures where real-time decisions must be made. Accordingly, the AAPM has initiated the publication of this Blue Paper of The Emerging Technology Working Group (TETAWG) and the creation of a Task Group from the Therapy Physics Committee within the Treatment Delivery Subcommittee. In describing the relevant issues, this document outlines the key parameters, stakeholders, impacts, and outcomes of clinical FGS technology and its applications. The presentation is not intended to be conclusive, but rather to inform the field of medical physics and stimulate the discussions needed in the field with respect to a seemingly low-risk imaging technology that has high potential for significant therapeutic impact. This AAPM Task Group is working toward consensus around guidelines and standards for advancing the field safely and effectively.

Single-pixel imaging (SPI) has attracted increasing attention in recent years because of its advantages in imaging systems. However, a low reconstruction quality and a long reconstruction time have hindered the development of SPI. Hence, in this study, we propose a Zernike SPI (ZSPI) technique to reduce the number of illumination patterns and reconstruction time whilst retaining robustness. First, the ZSPI technique was theoretically demonstrated. Phase-shifting Zernike moment projections were used to illuminate the target and an inverse Zernike transform was used to reconstruct the desired image. In order to prove the feasibility, numerical simulations were carried out with different sample ratios (SRs) ranging from 0.1 to 0.3; an acceptable reconstruction appeared at approximately 0.1. This result indicated that ZSPI could obtain satisfactory reconstruction results at low SRs. Further simulation and physical experiments were compared with different reconstruction algorithms, including noniterative, linear iterative, and nonlinear iterative methods under speckle modulation patterns at a sample of 0.1 in terms of different targets. The results revealed that ZSPI had a higher imaging quality and required less imaging time, particularly for low-frequency targets. The method presented in this study has advantages for the high-efficiency imaging of low-frequency targets, which can provide a new solution for the SPI method. [ABSTRACT FROM AUTHOR]

In the context of COVID-19, the research on various aspects of the venipuncture robot field has become increasingly hot, but there has been little research on robotic needle insertion angles, primarily performed at a rough angle. This will increase the rate of puncture failure. Furthermore, there is sometimes significant pain due to the patients' differences. This paper investigates the optimal needle entry angle decision for a dorsal hand intravenous injection robot. The dorsal plane of the hand was obtained by a linear structured light scan, which was used as a basis for calculating the needle entry angle. Simulation experiments were also designed to determine the optimal needle entry angle. Firstly, the linear structured optical system was calibrated and optimized, and the error function was constructed and solved iteratively by the optimization method to eliminate measurement error. Besides, the dorsal hand was scanned to obtain the spatial point clouds of the needle entry area, and the least squares method was used to fit it to obtain the dorsal hand plane. Then, the needle entry angle was calculated based on the needle entry area plane. Finally, the changes in the penetration force under different needle entry angles were analyzed to determine the optimal needle insertion angle. According to the experimental results, the average error of the optimized structured light plane position was about 0.1 mm, which meets the needs of the project, and a large angle should be properly selected for needle insertion during the intravenous injection. [ABSTRACT FROM AUTHOR]

Palmprint has been widely used in biometric systems because of its durability and reliability. To avoid recognition performance degradation, dynamic region of interest extraction is a critical step for these systems. In this study, a low-cost contactless palmprint imaging system has been designed and a dynamic region of interest extraction method has been applied to palmprints using the MediaPipe Hands framework. Since the need for hygienic touchless systems has been realized in the post-COVID-19 pandemic world, a low-cost imaging system has been proposed to capture the user's hand at a distance without touching any platform. The region of interest of the user's palmprints in a real-time video stream has been extracted dynamically. This study creates a paradigm for future studies on palmprint imaging. With conducted experiments, the potential of MediaPipe Hands in terms of speed and accuracy on mobile palmprint imaging applications has been realized on Raspberry Pi 4. This work demonstrates that the employed hardware and proposed hand-tracking algorithm are suitable for designing low-cost contactless palmprint imaging systems in non-controlled ambient light conditions. For recognition purposes, a database will be released soon. [ABSTRACT FROM AUTHOR]

Abstract Systems neuroscience is focused on how ensemble properties in the brain, such as the activity of neuronal circuits, gives rise to internal brain states and behavior. Many of the studies in this field have traditionally involved electrophysiological recordings and computational approaches that attempt to decode how the brain transforms inputs into functional outputs. More recently, systems neuroscience has received an infusion of approaches and techniques that allow the manipulation (e.g., optogenetics, chemogenetics) and imaging (e.g., two-photon imaging, head mounted fluorescent microscopes) of neurons, neurocircuits, their inputs and outputs. Here, we will review novel approaches that allow the manipulation and imaging of specific molecular mechanisms in specific cells (not just neurons), cell ensembles and brain regions. These molecular approaches, with the specificity and temporal resolution appropriate for systems studies, promise to infuse the field with novel ideas, emphases and directions, and are motivating the emergence of a molecularly oriented systems neuroscience, a new discipline that studies how the spatial and temporal patterns of molecular systems modulate circuits and brain networks, and consequently shape the properties of brain states and behavior.

Computational ghost imaging is a novel technique, which has a wide range of applications in many fields. As a key part of computational ghost imaging, the measurement matrix plays an important role in imaging quality and system practicability. To improve the imaging quality of computational ghost imaging and overcome the poor stability and non-negativity of the measurement matrix, we propose a new construction method for the deterministic measurement matrix based on the difference set modulo subgroup. This method uses an efficient simulated annealing algorithm to search for the difference set modulo subgroup. Then a 0–1 binary measurement matrix can be constructed according to the obtained difference set. We can show that the measurement matrix constructed by this method has low coherence and can satisfy the restricted isometry property. The simulation and experimental results showed that the reconstruction quality of the proposed measurement matrix was equivalent to the Sparse random matrix and better than the Toeplitz and Circulant matrices, which indicates the feasibility of the newly proposed measurement matrix.

Background: Manufacturing markings printed on products play an important role in the handling and use of pharmaceuticals and perishable foods. Currently, optical character recognition, neural networks, deep learning-based methods, and combinations of these methods are used to recognize these codes. Methods: This systematic review was performed to find papers that can answer the following research questions: How have machine vision methods that can recognize product texts evolved over the past eight years? What are the most common difficulties in recognizing product texts? Articles published between 2012 and 2020 were systematically searched from Science Direct/SCOPUS, and Google Scholar in November-December 2020. Ten studies were eligible, with inclusion criteria: details about the recognition method used, performance analysis result, imaging method, product and the text printed on it. Results: Product text recognition methods have evolved significantly over the last two years to tolerate the most common difficulties in the field. This is due to the ability of the deep learning neural network (DNN) architectures such as convolutional neural networks (CNN) to extract and learn salient character features straight from packaging surface images. Four of the most recent methods use two consecutive deep learning networks, one detecting the text area based on an image captured from the product package's surface and the other recognizing the characters within. Furthermore, this paper presents solutions to the most common product text recognition difficulties. Conclusions: There were a limited number of studies that met the eligibility criteria for this systematic review. The study's aim was to evaluate the development of machine vision methods for recognizing manufacturing marking texts printed on the surface of products. The study results demonstrated how methods have evolved over time, beginning with optical character recognition, and advancing to methods which can recognize texts despite the field's most common problems.

Major processed meat products, including minced beef, are one of the favorite ingredients of most people because they are high in protein, vitamins, and minerals. The high demand and high prices make processed meat products vulnerable to adulteration. In addition, eliminating morphological attributes makes the authenticity of minced beef challenging to identify with the naked eye. This paper aims to describe the feasibility study of adulteration detection in minced beef using a low-cost imaging system coupled with a deep neural network. The proposed method was expected to be able to detect minced beef adulteration. There were 500 captured images of minced beef samples. Then, there were 24 color and textural features retrieved from the image. The samples were then labeled and evaluated. A deep neural network (DNN) was developed and investigated to support classification. The proposed DNN was also compared to six machine learning algorithms in the form of accuracy, precision, and sensitivity of classification. The feature importance analysis was also performed to obtain the most impacted features to classification results. The DNN model classification accuracy was 98.00% without feature selection and 99.33% with feature selection. The proposed DNN has the best performance with individual accuracy of up to 99.33%, a precision of up to 98.68%, and a sensitivity of up to 98.67%. This work shows the enormous potential application of a low-cost imaging system coupled with DNN to rapidly detect adulterants in minced beef with high performance.

Background: Manufacturing markings printed on products play an important role in the handling and use of pharmaceuticals and perishable foods. Currently, optical character recognition, neural networks, deep learning-based methods, and combinations of these methods are used to recognize these codes. Methods: This systematic review was performed to find papers that can answer the following research questions: How have machine vision methods that can recognize product texts evolved over the past eight years? What are the most common difficulties in recognizing product texts? Articles published between 2012 and 2020 were systematically searched from Science Direct/SCOPUS, and Google Scholar in November-December 2020. Ten studies were eligible, with inclusion criteria: details about the recognition method used, performance analysis result, imaging method, product and the text printed on it. Results: Product text recognition methods have evolved significantly over the last two years to tolerate the most common difficulties in the field. This is due to the ability of the deep learning neural network (DNN) architectures such as convolutional neural networks (CNN) to extract and learn salient character features straight from packaging surface images. Four of the most recent methods use two consecutive deep learning networks, one detecting the text area based on an image captured from the product package's surface and the other recognizing the characters within. Furthermore, this paper presents solutions to the most common product text recognition difficulties. Conclusions: There were a limited number of studies that met the eligibility criteria for this systematic review. The study's aim was to evaluate the development of machine vision methods for recognizing manufacturing marking texts printed on the surface of products. The study results demonstrated how methods have evolved over time, beginning with optical character recognition, and advancing to methods which can recognize texts despite the field's most common problems.

The sCMOS imaging system with deep vacuum cooling technology has become a necessary way to improve the detection capability of space targets. In order to improve the detection capability of the photoelectric detection equipment for space targets, this paper developed the Highly Sensitive Deep Vacuum Cooling Imaging System (HSDVCIS). Firstly, we designed the imaging readout processing circuit using the GSENSE4040 sCMOS image sensor designed and manufactured by Gpixel and the deep vacuum cooling structure using thermoelectric cooling. Then, we tested the designed HSDVCIS with readout noise, dark current, and dynamic range of 3.96 e−, 0.12 e−/pixel/sec, and 84.49 dB, respectively, and tested the image sensor with a minimum cooling temperature of −40 °C. Finally, according to the results of observation experiments, we validated that the photoelectric detection equipment equipped with HSDVCIS improved the limiting detection magnitude (at SNR = 5 level) from 13.22 to 13.51 magnitudes within a 3 s exposure time by turning on the cooling function. Therefore, HSDVCIS designed in this paper can achieve highly sensitive detection of space targets. At the same time, the development of HSDVCIS also provides technical reserves and strong support for future research on the imaging systems using multiple image sensor mosaics.

2D vdWs heterostructure is realized as a powerful technique for tuning the optoelectronic properties and thus developing the future generation optoelectronic devices, especially for photodetectors. However, photodetectors based on 2D vdWs heterostructure suffer from responsivity, detectivity, and large photoresponse speed inhibits their applications in further diverse areas. Here, a graphene electrode-based InSe/WSe 2 vdWs heterostructure is proposed aiming to develop a high-performance photodetector. Owing to the graphene electrode, the heterostructure devices build a strong electronic field at the surface of the InSe/WSe 2 vdWs heterostructure. As a result, the device shows excellent optoelectronic characteristics such as broad band photoresponse ranging from 532 nm (visible) to 1100 nm (near infrared) including a high responsivity of 829.7 AW−1, a detectivity of 2.81×1014 Jones and a rapid photoresponse of 10 µs. Significantly, as presented photodetector device is applied in an imaging system, showcasing its capability for high-contrast photodetection. These findings highlight that the potential of graphene electrode integration in 2D vdWs heterostructure provides an effective roadmap for developing the advancing next generation of optoelectronic devices. [Display omitted] • Incorporating few layers of graphene in 2D heterostructure (InSe/WSe 2) aims aiming to develop high performance photodetector. • Achieved excellent optical parameters such as high responsivity, detectivity and shorter photoresponse at the same time. • As an application, the demonstrated device shows competitive high contrast imaging system. [ABSTRACT FROM AUTHOR]