Pixel Size Research Articles

CRITERIA FOR THE OPTIMAL MODE OF NON-DESTRUCTIVE TESTING BY DIGITAL RADIOGRAPHY

Theoretically justified and experimentally confirmed criteria for the selection of modes and parameters of digital radiography control. The analysis of the digital image quality showed its dependence on the parameters and control modes, on the value of the signal-to-noise ratio. Analytical information was obtained a relationship linking the size of the defect in the plane perpendicular to the axis of the radiation beam, the size of the focal spot of the radiation source, the parameters of the control circuit and the pixel size of the detector system. The validity of the analytical expression has been confirmed experimentally.

Inverse design of color routers in CMOS image sensors: toward minimizing interpixel crosstalk

Abstract Over the past decade, significant advancements in high-resolution imaging technology have been driven by the miniaturization of pixels within image sensors. However, this reduction in pixel size to submicrometer dimensions has led to decreased efficiency in color filters and microlens arrays. The development of color routers that operate at visible wavelengths presents a promising avenue for further miniaturization. Despite this, existing color routers often encounter severe interpixel crosstalk, around 70 %, due to the reliance on periodic boundary conditions. Here, we present interpixel crosstalk-minimized color routers that achieve an unprecedented in-pixel optical efficiency of 87.2 % and significantly reduce interpixel crosstalk to 2.6 %. The color routers are designed through adjoint optimization, incorporating customized incident waves to minimize interpixel crosstalks. Our findings suggest that our color router design surpasses existing color routing techniques in terms of in-pixel optical efficiency, representing a crucial step forward in the push toward commercializing the next generation of solid-state image sensors.

Klasifikasi Gender Berdasarkan Sidik Jari Menggunakan Principal Component Analysis dan Support Vector Machine

Most fingerprint classification research uses features such as core and delta as its basis. Before extracting fingerprint features, various preprocessing steps are usually performed first. This study differs from other studies in that classification is performed directly on the fingerprint image without going through a detailed preprocessing step and only a pixel size change is performed to 96x103. Fingerprint features are not determined manually, but are extracted automatically using the Principal Component Analysis (PCA) method which produces the 4200 best features. For feature perfection reasons, feature normalization has been performed using StandardScaler. The classification of this study uses a nonlinear Support Vector Machine (SVM) method with a Polynomial kernel. This study uses 6000 data samples from the SOCOFing database. This model obtains a classification accuracy of up to 88.75%.

Pixel-super-resolved lens-free quantitative phase microscopy with partially coherent illumination

Lens-free on-chip microscopy (LFOCM) has been widely utilized in digital pathology, drug screening, point-of-care testing (POCT), and quantitative phase imaging (QPI) due to its high throughput imaging capability and compactness. Initially, coherent laser sources were used in LFOCM to generate interference fringes to reconstruct the intensity and phase information of an object. The use of partially coherent light-emitting diodes (LEDs) in LFOCM offers a more portable and cost-effective alternative to conventional coherent illumination sources. However, the coherence-gating effect from a relatively low degree of coherence may cause a blur of high-frequency information in holograms, leading to an inaccurate object recovery. Thus, we present a pixel-super-resolved lens-free quantitative phase microscopy (PSR-LFQPM) with partially coherent illumination, which not only compensates for the impact of low coherence without increasing the volume of the system but also suppresses the theoretical Nyquist-Shannon sampling resolution limit imposed by the sensor pixel size (0.9 μm). Based on the partially coherent imaging model, we integrate the spatial coherence transfer function (SCTF) obtained from the pre-calibrated LED source distribution during the iteration process to obtain an accurate high-resolution recovery. Applying PSR-LFQPM to image living HeLa cells in vitro, we achieve real-time dynamic high-throughput QPI performance (half-pitch resolution of 780 nm with a 1.41-fold improvement compared to results without considering the effect of coherence) across a wide FOV (19.53 mm2). The proposed method provides a compact, low-cost, and high-throughput lens-free on-chip microscopy system for biomedical and POCT applications.

Ultrathin Graphite‐Based Full‐Color Electrochromic Devices

AbstractUltrathin graphite‐based materials have revolutionized optoelectronics through their multispectral and energy‐efficient tunability. However, their narrow color range poses a challenge in applications requiring a broad spectrum of colors for effective information delivery or aesthetic enhancement. Here, full‐color tunability is achieved in ultrathin graphite‐based electrochromic devices using Fabry‐Perot (F‐P) nanocavities. By adjusting the optical properties (n, k) of ultrathin graphite through lithium‐ion intercalation/de‐intercalation and the thickness of the dielectronic SiO2 layer, managed to control the optical reflectivity in the visible spectrum. Moreover, this prototype device consumes only 1.59 mW cm−2, just one‐tenth of the commercial organic light‐emitting displays’ energy usage. Furthermore, the pixel size in the Fabry‐Perot nanocavity‐type electrodes can be reduced to 2 µm, under half that of contemporary displays like Micro‐LED. These results pave the way for full‐color displays with minimal energy consumption and inspire extensive research in low‐power photonics.

A Robust Monocular and Binocular Visual Ranging Fusion Method Based on an Adaptive UKF.

Visual ranging technology holds great promise in various fields such as unmanned driving and robot navigation. However, complex dynamic environments pose significant challenges to its accuracy and robustness. Existing monocular visual ranging methods are susceptible to scale uncertainty, while binocular visual ranging is sensitive to changes in lighting and texture. To overcome the limitations of single visual ranging, this paper proposes a fusion method for monocular and binocular visual ranging based on an adaptive Unscented Kalman Filter (AUKF). The proposed method first utilizes a monocular camera to estimate the initial distance based on the pixel size, and then employs the triangulation principle with a binocular camera to obtain accurate depth. Building upon this foundation, a probabilistic fusion framework is constructed to dynamically fuse monocular and binocular ranging using the AUKF. The AUKF employs nonlinear recursive filtering to estimate the optimal distance and its uncertainty, and introduces an adaptive noise-adjustment mechanism to dynamically update the observation noise based on fusion residuals, thus suppressing outlier interference. Additionally, an adaptive fusion strategy based on depth hypothesis propagation is designed to autonomously adjust the noise prior of the AUKF by combining current environmental features and historical measurement information, further enhancing the algorithm's adaptability to complex scenes. To validate the effectiveness of the proposed method, comprehensive evaluations were conducted on large-scale public datasets such as KITTI and complex scene data collected in real-world scenarios. The quantitative results demonstrate that the fusion method significantly improves the overall accuracy and stability of visual ranging, reducing the average relative error within an 8 m range by 43.1% and 40.9% compared to monocular and binocular ranging, respectively. Compared to traditional methods, the proposed method significantly enhances ranging accuracy and exhibits stronger robustness against factors such as lighting changes and dynamic targets. The sensitivity analysis further confirmed the effectiveness of the AUKF framework and adaptive noise strategy. In summary, the proposed fusion method effectively combines the advantages of monocular and binocular vision, significantly expanding the application range of visual ranging technology in intelligent driving, robotics, and other fields while ensuring accuracy, robustness, and real-time performance.

Exploring CT pixel and voxel size effect on anatomic modeling in mandibular reconstruction

BackgroundComputer-aided modeling and design (CAM/CAD) of patient anatomy from computed tomography (CT) imaging and 3D printing technology enable the creation of tangible, patient-specific anatomic models that can be used for surgical guidance. These models have been associated with better patient outcomes; however, a lack of CT imaging guidelines risks the capture of unsuitable imaging for patient-specific modeling. This study aims to investigate how CT image pixel size (X-Y) and slice thickness (Z) impact the accuracy of mandibular models.MethodsSix cadaver heads were CT scanned at varying slice thicknesses and pixel sizes and turned into CAD models of the mandible for each scan. The cadaveric mandibles were then dissected and surface scanned, producing a CAD model of the true anatomy to be used as the gold standard for digital comparison. The root mean square (RMS) value of these comparisons, and the percentage of points that deviated from the true cadaveric anatomy by over 2.00 mm were used to evaluate accuracy. Two-way ANOVA and Tukey-Kramer post-hoc tests were used to determine significant differences in accuracy.ResultsTwo-way ANOVA demonstrated significant difference in RMS for slice thickness but not pixel size while post-hoc testing showed a significant difference in pixel size only between pixels of 0.32 mm and 1.32 mm. For slice thickness, post-hoc testing revealed significantly smaller RMS values for scans with slice thicknesses of 0.67 mm, 1.25 mm, and 3.00 mm compared to those with a slice thickness of 5.00 mm. No significant differences were found between 0.67 mm, 1.25 mm, and 3.00 mm slice thicknesses. Results for the percentage of points deviating from cadaveric anatomy greater than 2.00 mm agreed with those for RMS except when comparing pixel sizes of 0.75 mm and 0.818 mm against 1.32 mm in post-hoc testing, which showed a significant difference as well.ConclusionThis study suggests that slice thickness has a more significant impact on 3D model accuracy than pixel size, providing objective validation for guidelines favoring rigorous standards for slice thickness while recommending isotropic voxels. Additionally, our results indicate that CT scans up to 3.00 mm in slice thickness may provide an adequate 3D model for facial bony anatomy, such as the mandible, depending on the clinical indication.

Analisis Komparatif Tutupan Mangrove Menggunakan Citra Landsat 9 dan Sentinel 2A di Desa Labuan Tereng Kabupaten Lombok Barat

Labuan Tereng Village is a place where mangrove vegetation grows and develops. The location close to the harbor sheet makes the mangrove ecosystem damaged by port activities. High port activity can disrupt the condition of mangrove ecosystem development in Labuan Tereng Village. This study was conducted to evaluate mangrove health by looking at canopy cover or canopy density using the Hemispherical Photography method analyzed using Landsat 9 and Sentinel 2A to assess the extent of relationship between mangrove canopy cover and images. The findings revealed that the mean mangrove cover density value of 66% which is included in the medium category. Statistical analysis of several vegetation indexes with mangrove cover obtained the highest linear regression results in the SAVI model with a value of 0,41 for Landsat 9 images and 0,65 for Sentinel 2A images. The results of image data analysis on Sentinel 2A show a smaller pixel size value and contain more pixels so as to produce better and complex data analysis when compared to Landsat 9 imagery.

An enhanced and expanded Toolbox for River Velocimetry using Images from Aircraft (TRiVIA)

AbstractDetailed, accurate information on flow patterns in river channels can improve understanding of habitat conditions, geomorphic processes, and potential hazards to help inform water management. Data describing flow patterns in river channels can be obtained efficiently via image‐based techniques that have become more widely used in recent years as the number of platforms for acquiring images has expanded and the number of algorithms for inferring velocities has grown. Image‐based techniques have been incorporated into various software packages, including the Toolbox for River Velocimetry using Images from Aircraft (TRiVIA). TRiVIA is a freely available, standalone computer program that provides a comprehensive workflow for performing particle image velocimetry (PIV)‐based analyses within a graphical interface. This paper summarizes major enhancements incorporated into the latest release of TRiVIA, version 2.1. For example, a new Tool for Input Parameter Selection (TIPS) provides guidance for specifying key inputs to the PIV algorithm by allowing users to explore relationships between flow velocity, pixel size, output vector spacing, and frame interval. Improved visualization capabilities include the ability to create streamlines and display PIV output on an interactive web map. The program now provides greater flexibility for importing field data in various formats and selecting which observations to use for accuracy assessment. The most substantial additions to TRiVIA 2.1 are the ability to integrate bathymetric information with image‐derived velocity estimates to calculate river discharge and to use images acquired from moving aircraft to efficiently map long segments of large rivers to support habitat assessment, contaminant transport studies, and a range of other applications.

Novel multi-frame super resolution algorithm for X-ray diffraction (XRD)

The spatial distribution of signals in X-ray diffraction (XRD) may be very narrow, posing challenges in obtaining high angular resolution results through traditional methods. This article explores multi-frame super-resolution algorithms from the field of image processing, selecting and refining the best suited to the requirements of the crystal truncation rod (CTR) test. Consequently, a new algorithm with a corresponding methodology is proposed. This approach is subsequently applied to characterize the CTR signal of SrTiO3 single-crystal samples, effectively enhancing the clarity of blurry and rough CTR cross-section signals. The resolution with this method surpasses that obtained using the pixel size alone, which is beneficial for characterizing weak signals. By combining data in three dimensions, a significantly enhanced three-dimensional CTR signal is obtained. This method enables the extraction of otherwise difficult-to-obtain information and can be conveniently integrated into subsequent theoretical work. Moreover, these methods hold potential for application in other techniques that require improved resolution under similar conditions.

A scattered volume emitter micropixel architecture for ultra efficient light extraction from DUV LEDs

Deep ultraviolet light-emitting diodes (DUV LEDs) typically suffer from strong parasitic absorption in the p-epitaxial layer and rear metal contact/mirror. This problem is exacerbated by a substantial portion of the multiple quantum well (MQW) emissions having a strong out-of-plane dipole component, contributing to emission in widely oblique directions outside the exit cone of the front semiconductor emitting surface. To address this, we propose an architecture that leverages such a heavily oblique angular emission profile by utilizing spaced-apart or scattered volume emitter micropixels that are embedded in a low-index dielectric buffer film with a patterned top surface. This approach achieves high light extraction efficiency at the expense of enlarging the effective emission area, however, it does not require a high-index (e.g., sapphire) substrate or a lens or a nanotextured epi for outcoupling purposes. Hybrid wave and ray optical simulations demonstrated a remarkable larger than three to sixfold increase in light extraction efficiency as compared to that of a conventional planar LED design with a sapphire substrate depending on the assumed epi layer absorption, pixel size, and ratio of light emission area to the MQW active area. An extraction efficiency three times greater than that of a recent nanotextured DUV LED design was also demonstrated. This architecture paves the way for DUV LEDs to have a plug efficiency comparable to that of mercury lamps while being significantly smaller.

Y-90 PET/MR imaging optimization with a Bayesian penalized likelihood reconstruction algorithm.

Positron Emission Tomography (PET) imaging after Y liver radioembolization is used for both lesion identification and dosimetry. Bayesian penalized likelihood (BPL) reconstruction algorithms are an alternative to ordered subset expectation maximization (OSEM) with improved image quality and lesion detectability. The investigation of optimal parameters for Y image reconstruction of Q.Clear, a commercial BPL algorithm developed by General Electric (GE), in PET/MR is a field of interest and the subject of this study. The NEMA phantom was filled at an 8:1 sphere-to-background ratio. Acquisitions were performed on a PET/MR scanner for clinically relevant activities between 0.7 and 3.3 MBq/ml. Reconstructions with Q.Clear were performed varying the penalty parameter between 20 and 6000, the acquisition time between 5 and 20 min and pixel size between 1.56 and 4.69 mm. OSEM reconstructions of 28 subsets with 2 and 4 iterations with and without Time-of-Flight (TOF) were compared to Q.Clear with = 4000. Recovery coefficients (RC), their coefficient of variation (COV), background variability (BV), contrast-to-noise ratio (CNR) and residual activity in the cold insert were evaluated. Increasing parameter lowered RC, COV and BV, while CNR was maximized at = 4000; further increase resulted in oversmoothing. For quantification purposes, = 1000-2000 could be more appropriate. Longer acquisition times resulted in larger CNR due to reduced image noise. Q.Clear reconstructions led to higher CNR than OSEM. A of 4000 was obtained for optimal image quality, although lower values could be considered for quantification purposes. An optimal acquisition time of 15 min was proposed considering its clinical use.

Lateral Confinement in 2D Nanoplatelets: A Strategy to Expand the Colloidal Quantum Engineering Toolbox

AbstractAmong colloidal nanocrystals, 2D nanoplatelets offer a unique set of properties with exceptionally narrow luminescence and low lasing thresholds. Furthermore, their anisotropic shape expands the playground for the complex design of heterostructures where spectra but also scattering rates can be engineered. A challenge that still remains is to combine shell growth which makes NPLs stable, with spectral tunability. Indeed, most reported shelled nanoplatelets end up being red emitters due to a loss of quantum confinement. Here, the combination of both lateral and in‐plane confinements within a single heterostructure is explored. A CdS/CdSe/CdS/CdZnS core–crown–crown shell structure that enables yellow emission is grown and that is responsive to a large range of excitation including visible photons, X‐ray photons, electron beams, and electrical excitations. k.p simulations predict that emission tunability of up to several 100 s of meV can be obtained in ideal structures. This material also displays stimulated emission resulting from bi‐exciton emission with a low threshold. Once integrated into an LED stack, this material is compatible with sub‐bandgap excitation and exhibits high luminance. Scaling of the electroluminescence properties by downsizing the pixel size is also investigated.

3D electronic implants in subretinal space: Long-term follow-up in rodents

Clinical results with photovoltaic subretinal prosthesis (PRIMA) demonstrated restoration of sight via electrical stimulation of the interneurons in degenerated retina, with resolution matching the 100 μm pixel size. Since scaling the pixels below 75 μm in the current bipolar planar geometry will significantly limit the penetration depth of the electric field and increase stimulation threshold, we explore the possibility of using smaller pixels based on a novel 3-dimensional honeycomb-shaped design. We assessed the long-term biocompatibility and stability of these arrays in rats by investigating the anatomical integration of the retina with flat and 3D implants and response to electrical stimulation over lifetime – up to 32–36 weeks post-implantation in aged rats. With both flat and 3D implants, signals elicited in the visual cortex decreased after the day of implantation by more than 3-fold, and gradually recovered over the next 12–16 weeks. With 25 μm high honeycomb walls, the majority of bipolar cells migrate into the wells, while amacrine and ganglion cells remain above the cavities, which is essential for selective network-mediated stimulation of the retina. Retinal thickness and full-field stimulation threshold with 40 μm-wide honeycomb pixels were comparable to those with planar devices – 0.05 mW/mm2 with 10 ms pulses. However, fewer cells from the inner nuclear layer migrated into the 20 μm-wide wells, and stimulation threshold increased over 12–16 weeks, before stabilizing at about 0.08 mW/mm2. Such threshold is still significantly lower than 1.8 mW/mm2 with a previous design of flat bipolar pixels, confirming the promise of the 3D honeycomb-based approach to high resolution subretinal prosthesis.

Image up-sampling method for dual-radiation nondestructive cargo inspection system

In this paper, an image up-sampling method for a dual-radiation nondestructive cargo inspection system, that uses x-ray and neutron, is proposed. The inspection system is assumed to have a larger neutron detector pixel size than that of x-ray detector pixel, which is usually the case to address the lower neutron source flux and the lower detector efficiency than those in the x-ray imaging system. The proposed technique adopts a cluster map of an x-ray projection image with high spatial resolution to up-sample the corresponding neutron projection image with low spatial resolution. The cluster map is acquired by use of a modified k-means clustering algorithm. The up-sampling process is formulated by a linear least-square problem of mapping the neutron projection image onto the cluster map. Consequently, the neutron projection image would have the same dimension with the x-ray projection image array allowing R-value based material decomposition. We have conducted a numerical study using GATE simulation to demonstrate the efficacy of the proposed method. The proposed method was compared with a linear interpolation method and also with an up-sampling technique that does not use the cluster map. The outperformance of the proposed method over those reference techniques has been successfully presented.

Compact Numerical Aperture 0.5 Fiber Optic Spectrometer Design Using Active Image Plane Tilt.

The numerical aperture of the spectrometer is crucial for weak signal detection. The transmission lens-based configuration has more optimization variations, and the grating can work approximately in the Littrow condition; thus, it is easier to acquire high numerical aperture (NA). However, designing a large aperture focusing lens remains challenging, and thus, ultra-high NA spectrometers are still difficult to acquire. In this paper, we propose a method of setting image plane tilt ahead directly when designing the large aperture focusing lens to simplify the high NA spectrometer design. By analyzing the accurate demands of the focusing lens, it can be concluded that a focusing lens with image plane tilt has much weaker demand for achromatism, and other monochromatic aberration can also be reduced, which is helpful to increase the NA. An NA0.5 fiber optic spectrometer design is given to demonstrate the proposed method. The design results show that the NA can achieve 0.5 using four lenses of two materials, and the MTF is higher than 0.5 when the spectral dispersion length is 12.5 mm and the pixel size is 25 μm, and thus, the spectral resolution can achieve 6.5 nm when the spectral sampling ratio is 2:1. The proposed method can provide reference for applications when appropriate materials are limited and high sensitivity is necessary.

Mapping Maize Evapotranspiration with Two-Source Land Surface Energy Balance Approaches and Multiscale Remote Sensing Imagery Pixel Sizes: Accuracy Determination toward a Sustainable Irrigated Agriculture

Mapping Maize Evapotranspiration with Two-Source Land Surface Energy Balance Approaches and Multiscale Remote Sensing Imagery Pixel Sizes: Accuracy Determination toward a Sustainable Irrigated Agriculture

Tandem mass spectrometry imaging to assess illudin S distributions in Omphalotus illudens mushrooms

Poisoning metabolites within mushrooms typically exert varying physiological and biological effects; however, their distributions within mushrooms are seldom investigated. This study focused on imaging illudin S, a representative poisoning metabolite within Omphalotus illudens mushroom, using desorption electrospray ionization–tandem mass spectrometry (DESI–MS/MS) coupled with liquid chromatography–electrospray ionization–tandem mass spectrometry (LC–ESI–MS/MS). Initially, LC–ESI–MS/MS conditions were established for the selective detection of illudin S (m/z 247→159, positive mode) from extracted mushroom. Based on this MS/MS condition, each mushroom was divided into nine sections, and each section was subjected to specific DESI–MS/MS mode imaging (pixel size: 200 × 200 μm). The results revealed high concentrations of illudin S in the stalks of the mushrooms growing on trees. Further, re-evaluations using the LC–MS/MS assay revealed a seven-fold difference in the illudin S between the stalk and other regions. This study marks the first attempt at assessing toxic metabolite distributions within poisonous mushrooms, thus offering valuable insights including the efficient utilization of illudin analogs in biological applications.

71‐1: CMOS Backplane Technology and Its Challenge for µLEDoS AR/XR Display

This paper introduces the latest CMOS (Complementary Metal‐Oxide‐Silicon) backplane technology for µLEDoS AR/XR display engines. The backplane supports a display resolution of 1,280RGB x 720 and has been implemented on a 28nm Fully Depleted Silicon on Insular (FD‐SOI) CMOS process in order to meet the requirements such as performance, power, and pixel size. The area of a single pixel is 4.95µm x 4.95µm achieving higher than 5,000 PPI in RGB‐color mode. Each pixel contains 3 independent sub‐pixel drivers and one dependent driver assigned for a red LED. Each sub‐pixel driver includes a 10‐bit video SRAM memory, PWM (Pulse Width Modulation) control logic block, a constant current generator, and LED driver stage to drive red, green, or blue LEDs. The backplane also integrates necessary image processing functions such as De‐mura compensation, dead‐pixel compensation, and digital gamma generation. The top surface of the backplane wafer is also prepared for a wafer‐to‐wafer hybridization bonding between the CMOS wafer and an LED wafer.

P‐141: Ultrafine‐pitch AlGaN Ultraviolet‐C microLED Displays for Quantum Dots Color Conversion

Aluminum Gallium Nitride (AlGaN) ultraviolet‐C (UV‐C) micro‐light‐emitting diodes (microLEDs) offer significant advantages in terms of convenience, cost‐effectiveness, and environmental friendliness, positioning them as promising candidates for display applications. However, achieving the desired high efficiency and scalability for large displays with ultra‐fine pixels necessitates substantial progress beyond current experimental outcomes. This study showcases the application of AlGaN UV‐C microLED display panels and micro‐displays incorporating quantum dots (QDs) for color conversion. Sidewall treatment and atomic layer deposited (ALD) passivation effectively address dangling bonds and etching damages, leading to a notable enhancement of TM‐polarized light extraction efficiency (LEE). Moreover, dedicated strain modulation efforts successfully reduce the high Al content (over 50%) wafer bowling effect, facilitating the modularization of ultrafine‐pitch AlGaN UV‐C microLED panels. Consequently, the devices achieve a peak performance of over 5% external quantum efficiency (EQE) as the mesa size scales down to 3 μm. The highlighted 0.18‐inch UV‐C microLED display panels, featuring a 9 μm pixel size, are precisely controlled by a CMOS IC driver to achieve desired patterns. Serving as an efficient pumping source for perovskite quantum dots paper (PQDP), this UV‐C microLED display suggests the potential to revolutionize the full‐color display industry by providing an innovative and unconventional solution.