Performance Of Imaging System Research Articles

An integrated imaging sensor for aberration-corrected 3D photography

Planar digital image sensors facilitate broad applications in a wide range of areas1–5, and the number of pixels has scaled up rapidly in recent years2,6. However, the practical performance of imaging systems is fundamentally limited by spatially nonuniform optical aberrations originating from imperfect lenses or environmental disturbances7,8. Here we propose an integrated scanning light-field imaging sensor, termed a meta-imaging sensor, to achieve high-speed aberration-corrected three-dimensional photography for universal applications without additional hardware modifications. Instead of directly detecting a two-dimensional intensity projection, the meta-imaging sensor captures extra-fine four-dimensional light-field distributions through a vibrating coded microlens array, enabling flexible and precise synthesis of complex-field-modulated images in post-processing. Using the sensor, we achieve high-performance photography up to a gigapixel with a single spherical lens without a data prior, leading to orders-of-magnitude reductions in system capacity and costs for optical imaging. Even in the presence of dynamic atmosphere turbulence, the meta-imaging sensor enables multisite aberration correction across 1,000 arcseconds on an 80-centimetre ground-based telescope without reducing the acquisition speed, paving the way for high-resolution synoptic sky surveys. Moreover, high-density accurate depth maps can be retrieved simultaneously, facilitating diverse applications from autonomous driving to industrial inspections.

Navigation accuracy and assessability of carbon fiber-reinforced PEEK instrumentation with multimodal intraoperative imaging in spinal oncology

Radiolucent carbon-fiber reinforced PEEK (CFRP) implants have helped improve oncological follow-up and radiation therapy. Here, we investigated the performance of 3D intraoperative imaging and navigation systems for instrumentation and precision assessment of CFRP pedicle screws across the thoraco-lumbar spine. Thirty-three patients with spinal tumors underwent navigated CFRP instrumentation with intraoperative CT (iCT), robotic cone-beam CT (rCBCT) or cone-beam CT (CBCT) imaging. Two different navigation systems were used for iCT-/rCBCT- and CBCT-based navigation. Demographic, clinical and outcome data was assessed. Four blinded observers rated image quality, assessability and accuracy of CFRP pedicle screws. Inter-observer reliability was determined with Fleiss` Kappa analysis. Between 2018 and 2021, 243 CFRP screws were implanted (iCT:93, rCBCT: 99, CBCT: 51), of which 13 were non-assessable (iCT: 1, rCBCT: 9, CBCT: 3; *p = 0.0475; iCT vs. rCBCT). Navigation accuracy was highest using iCT (74%), followed by rCBCT (69%) and CBCT (49%) (*p = 0.0064; iCT vs. CBCT and rCBCT vs. CBCT). All observers rated iCT image quality higher than rCBCT/CBCT image quality (*p < 0.01) but relevant pedicle breaches were reliably identified with substantial agreement between all observers regardless of the imaging modality. Navigation accuracy for CFRP pedicle screws was considerably lower than expected from reports on titanium implants and CT may be best for reliable assessment of CFRP materials.

Re-Calibration and Lens Array Area Detection for Accurate Extraction of Elemental Image Array in Three-Dimensional Integral Imaging

This paper presents a new method for extracting an elemental image array in three-dimensional (3D) integral imaging. To reconstruct 3D images in integral imaging, as the first step, a method is required to accurately extract an elemental image array from a raw captured image. Thus, several methods have been discussed to extract an elemental image array. However, the accuracy is sometimes degraded due to inaccurate edge detection, image distortions, optical misalignment, and so on. Especially, small pixel errors can deteriorate the performance of an integral imaging system with a lens array. To overcome the problem, we propose a postprocessing method for the accurate extraction of an elemental image array. Our method is a unified version of an existing method and proposed postprocessing techniques. The proposed postprocessing consists of re-calibration and lens array area detection. Our method reuses the results from an existing method, and it then improves the results via the proposed postprocessing techniques. To evaluate the proposed method, we perform optical experiments for 3D objects and provide the resulting images. The experimental results indicate that the proposed postprocessing techniques improve an existing method for extracting an elemental image array in integral imaging. Therefore, we expect the proposed techniques to be applied to various applications of integral imaging systems

Performance Evaluation of an Ultrasonic Imaging System Using Tissue-Mimicking Phantoms for Quality Assurance

Diagnostic ultrasound or sonography is an image that can provide valuable information for diagnosing and treating a variety of diseases and conditions. The aim of this research study is to examine the performance and accuracy of the ultrasonic imaging system for the guarantee of diagnosis quality assurance, and to adjust the penetration settings to minimize the time of repeat scans and maintenance duration during research experiments. Measurements in this experiment included the resolution (axial and lateral) and focal zones. Moreover, the evaluation was done by completing all the measurements at different depths on a multipurpose phantom model 539. The phantom was bought from the market and was not fabricated by the author. The measurements were achieved by applying two different transducers: curved and linear (flat). The ultrasound images were obtained and tested by using calipers (electronic), and the estimations and observations were read by using all the taken measurements and images. As a result, because the phantom depths were different, the penetration settings were different too, indicating that the depth impacted the penetrations of the created ultrasound image. Moreover, after the comparison of the recorded measurements and results, it was found that all measurements were within the accepted (standard) value and that the true value was specified by the production of the phantom.

An LED-Based structured illumination microscope using a digital micromirror device and GPU accelerated image reconstruction.

When combined with computational approaches, fluorescence imaging becomes one of the most powerful tools in biomedical research. It is possible to achieve resolution figures beyond the diffraction limit, and improve the performance and flexibility of high-resolution imaging systems with techniques such as structured illumination microscopy (SIM) reconstruction. In this study, the hardware and software implementation of an LED-based super-resolution imaging system using SIM employing GPU accelerated parallel image reconstruction is presented. The sample is illuminated with two-dimensional sinusoidal patterns with various orientations and lateral phase shifts generated using a digital micromirror device (DMD). SIM reconstruction is carried out in frequency space using parallel CUDA kernel functions. Furthermore, a general purpose toolbox for the parallel image reconstruction algorithm and an infrastructure that allows all users to perform parallel operations on images without developing any CUDA kernel code is presented. The developed image reconstruction algorithm was run separately on a CPU and a GPU. Two different SIM reconstruction algorithms have been developed for the CPU as mono-thread CPU algorithm and multi-thread OpenMP CPU algorithm. SIM reconstruction of 1024 × 1024 px images was achieved in 1.49 s using GPU computation, indicating an enhancement by ∼28 and ∼20 in computation time when compared with mono-thread CPU computation and multi-thread OpenMP CPU computation, respectively.

Performance of a scintillation imaging system for relative dosimetry in pencil beam scanning proton therapy

The proton spot scanning system requires extensive periodic quality assurance procedures to guarantee the conformality of planned dose distribution to the tumor. Detectors with stable, accurate, and fast data acquisition properties make the quality assurance procedures more efficient. For this purpose, a camera-based scintillation imaging system has been developed. A high scintillation efficiency screen coupled with a high-performance camera improved the dose sensitivity and precision required for the measurements. The dose distribution within the scintillating screen can be analyzed from the captured light distribution image in a relatively straightforward way.In this study, we investigated the performance of a 2D detection system by using a scintillating screen (silver-activated zinc sulfide powder deposited on the surface of a plastic scintillator HND-S2) for dose distribution measurement. The characteristics of the system in terms of response reproducibility, linear dose–response, and beam spot size dependence on proton dose were assessed in a series of proton irradiations. To evaluate the accuracy of lateral dose profiles measured by the ZnS: Ag based scintillating screen, we compared the results with plastic scintillator BC-408 and some commercial quality control devices. Several measurements were conducted with proton energies ranging from 70–235 MeV. We found that the detector showed stable response reproducibility (better than 1.6%) and good dose–response linearity (R2¿0.999). The beam spot size was independent of proton dose when the response of the pixel value was between 10% and 90% of the maximum. The in-air spot size measured by the ZnS: Ag based scintillating screen was found to be slightly smaller than the Lynx detector while the BC-408 showed a slightly bigger spot size. The inter-comparison results for scanned fields showed good agreements. The observed differences in beam profile measurement between the inorganic and organic scintillating screens were mainly due to their optical properties and structures. The developed scintillation imaging system with an effective resolution of 0.12 mm proved to be a reliable device for efficiently performing the quality checks for two-dimensional proton dosimetry.

Optimization method of the thermal control index of space remote sensors based on force-thermal coupling algorithm

To ensure the successful completion of space observation tasks, the temperatures of optical remote sensors must be maintained within appropriate ranges using thermal control systems to avoid the influence of the space thermal environment on imaging performance. In engineering, an appropriate temperature range must be accurately predicted for a remote sensor in orbit through a reasonable thermal control index to guide the design and optimization of the thermal control system. This study analyzes the environmental differences between systems in space and on Earth, calculates the temperature requirements of the imaging performance index as a constraint, investigates the coupling influence mechanism of gravity release and temperature change on system imaging performance, and proposes a method to optimize the thermal control index of a remote sensor. The proposed method can optimize the thermal control design to obtain sufficientimaging performance in orbit, reduce the thermal control power consumption by approximately 20%, and shorten the development cycle; it is also suitable for various types of remote sensors. This study verifies the rationality of the method through a combination of an orbital thermal simulation and a thermal vacuum test.

An Overview on Down-Looking UAV-Based GPR Systems

Radar imaging from unmanned aerial vehicles (UAVs) is a dynamic research topic attracting huge interest due to its practical fallouts. In this context, this article provides a comprehensive review of the current state of the art and challenges related to UAV-based ground-penetrating radar (GPR) imaging systems. First, a description of the available prototypes is provided in terms of radar technology, UAV platforms, and navigation control devices. Afterward, the paper addresses the main issues affecting the performance of UAV-based GPR imaging systems. such as the control of the UAV platform during the flight to collect high-quality data, the necessity to provide accurate platform position information in terms of probing wavelength, and the mitigation of clutter and other electromagnetic disturbances. A description of the major applicative areas for UAV GPR systems is reported with the aim to show their potential. Furthermore, the main signal-processing approaches currently adopted are detailed and two experimental tests are also reported to prove the actual imaging capabilities. Finally, open challenges and future perspectives regarding this promising technology are discussed.

Bullseye EVD: preclinical evaluation of an intra-procedural system to confirm external ventricular drainage catheter positioning.

External ventricular drainage (EVD) is a life-saving procedure indicated for elevated intracranial pressure. A catheter is inserted into the ventricles to drain cerebrospinal fluid and release the pressure on the brain. However, the standard freehand EVD technique results in catheter malpositioning in up to 60.1% of procedures. This proof-of-concept study aimed to evaluate the registration accuracy of a novel image-based verification system "Bullseye EVD" in a preclinical cadaveric model of catheter placement. Experimentation was performed on both sides of 3 cadaveric heads (n = 6). After a pre-interventional CT scan, a guidewire simulating the EVD catheter was inserted as in a clinical EVD procedure. 3D structured light images (Einscan, Shining 3D, China) were acquired of an optical tracker placed over the guidewire on the surface of the scalp, along with three distinct cranial regions (scalp, face, and ear). A computer vision algorithm was employed to determine the guidewire position based on the pre-interventional CT scan and the intra-procedural optical imaging. A post-interventional CT scan was used to validate the performance of the Bullseye optical imaging system in terms of trajectory and offset errors. Optical images which combined facial features and exposed scalp within the surgical field resulted in the lowest trajectory and offset errors of 1.28° ± 0.38° and 0.33 ± 0.19mm, respectively. Mean duration of the optical imaging procedure was 128 ± 35s. The Bullseye EVD system presents an accurate patient-specific method to verify freehand EVD positioning. Use of facial features was critical to registration accuracy. Workflow automation and development of a user interface must be considered for future clinical evaluation.

High-resolution integral imaging display with precise light control unit and error compensation

3D resolution is an important display performance of integral imaging system. In this paper, an integral imaging system with improved resolution was proposed by using precise light control and error compensation. In the proposed system, a precise light control unit was used instead of the conventional diffused backlight unit, so as to reduce the voxel size. Additionally, an error compensation method was proposed to avoid the mismatch between the pitches of the lens array and the elemental image array, so as to eliminate the crosstalk of reconstructed 3D images. In the optical experiment, a prototype was developed using the proposed structure and error compensation method. It reconstructed vivid 3D images with higher resolution and less crosstalk compared to the conventional system.

Sistem Keamanan Untuk Otorisasi Pada Smart Home Menggunakan Pengenalan Wajah Dengan Library OpenCV

As industrial 4.0 advances such as Internet of Things (IoT), Big Data, Cloud Computing , and Artificial Intelligent (AI) has prompted reseachers to innovate in various fields, including security systems. The security system is an important issue due to rise of theft in a residence. A security system is needed for home authorizon to prevent the crime of theft. Security systems are built using facial recognition. The research proposes to develop a security system using facial recognition based Raspberry Pi with Python programming and utilize the OpenCV. System testing includes training function testing, facial recognition function, image delevery function, decision-making function, and system performance testing, system performance for facial recognition is calculated using confusion matrix formula that produces 100% sensitivity, 13% specitificity, and 97% accuracy.&#x0D;

Operational Learning-Based Boundary Estimation in Electromagnetic Medical Imaging

Incorporating boundaries of the imaging object as <i>a priori</i> information to imaging algorithms can significantly improve the performance of EM medical imaging systems. To avoid overly complicating the system by using different sensors and the adverse effect of the subject&#x2019;s movement, a learning-based method is proposed to estimate the boundary (external contour) of the imaged object using the same EM imaging data. While imaging techniques may discard the reflection coefficients for being dominant and uninformative for imaging, these parameters are made use of for boundary detection. The learned model is verified through independent clinical human trials by using a head imaging system with a 16-element antenna array that works across the band 0.7&#x2013;1.6 GHz. The evaluation demonstrated that the model achieves average dissimilarity of 0.012 in Hu-moment while detecting head boundary. The model enables fast scan and image creation while eliminating the need for additional devices for accurate boundary estimation.

X-ray image chain synchronization control scheme design and performance evaluation

This paper describes the working principle of the image chain’s imaging system and analyzes the two imaging modes of the X-ray source as well as the two synchronization modes of the flat panel detector, with the goal of completing the design of the image chain’s system imaging. Two schemes of synchronous control of the image chain, hardware control and software control, are achieved on the basis of the design of the image chain’s imaging system. According to the experimental results, the hardware synchronization control, in comparison with the software synchronization control, enormously reduces the X-ray radiation time and the radiation received by the object as well as generating a lower CPU occupancy rate, which improves the safety of the performance of the image chain imaging system. Therefore, it can be concluded that hardware synchronization control is safer and more practical than software synchronization control. Lightweight cone-beam CT can be developed for use in mobile field hospitals and intensive care units to reduce the difficulty of doctors’ operations.

Experimentally validated x-ray image simulations of 50 μm x-ray PIV tracer particles

We evaluate Beer–Lambert (BL) ray-tracing and Monte Carlo N-Particle (MCNP) photon tracking simulations for prediction and comparison of x-ray imaging system performance. These simulation tools can aid the methodical design of laboratory-scale x-ray particle image velocimetry (XPIV) experiments and tracer particles by predicting image quality. Particle image signal-to-noise ratio (SNR) is used as the metric of system performance. Simulated and experiment data of hollow, silver-coated, glass sphere tracer particles (AGSF-33) are compared. As predicted by the simulations, the AGSF-33 particles are visible with a SNR greater than unity in 100 ms exposure time images, demonstrating their potential as x-ray PIV or particle tracking velocimetry (XPTV) tracers. The BL approach predicts the image contrast, is computationally inexpensive, and enables the exploration of a vast parameter space for system design. MCNP simulations, on the other hand, predict experiment images slightly more accurately, but are more than an order of magnitude more computationally expensive than BL simulations. For most practical XPIV system design applications, the higher computational expense of MCNP is likely not justified by the modest accuracy improvement compared to BL.

Image Quality and System Performance XIX Conference Overview and Papers Program

We live in a visual world. The perceived quality of images is of crucial importance in industrial, medical, and entertainment application environments. Developments in camera sensors, image processing, 3D imaging, display technology, and digital printing are enabling new or enhanced possibilities for creating and conveying visual content that informs or entertains. Wireless networks and mobile devices expand the ways to share imagery and autonomous vehicles bring image processing into new aspects of society. The power of imaging rests directly on the visual quality of the images and the performance of the systems that produce them. As the images are generally intended to be viewed by humans, a deep understanding of human visual perception is key to the effective assessment of image quality.

Modeling and evaluation of performance of dual field-of-view common-aperture dual-band imaging system

For the modeling and evaluation of dual field-of-view (FOV) common-aperture dual-band imaging system performance, two factors must be considered at the same time. One is that the system must have a larger target acquisition range, and the other is that the detection range and recognition range of the system must be the same. In this paper, taking the dual FOV common-aperture visible/long-wave infrared (LWIR) imaging system as an example, the performance of the dual FOV common-aperture dual-band imaging system is modeled and evaluated using an imaging system performance model based on comprehensive resolution. Firstly, the target acquisition range of the dual FOV visible imaging system is analyzed, and the condition that the detection range is equal to the recognition range is obtained. Then, under the condition of common aperture, the target acquisition range and the relationship between detection range and recognition range of dual FOV LWIR imaging system are analyzed. The analysis results show that, under the condition of dual FOV and common aperture, when the detection and recognition ranges of the visible imaging system are equal, the detection and recognition ranges of the LWIR imaging system are not equal. When the detection and recognition ranges are close by reducing the comprehensive resolution, the target acquisition range of the dual FOV common-aperture dual-band imaging system will decrease.

Evolving Fusion-Based Visibility Restoration Model for Hazy Remote Sensing Images Using Dynamic Differential Evolution

Remote sensing images taken during poor environmental conditions are degraded by the scattering of atmospheric particles, which affects the performance of many imaging systems. Hence, an efficient visibility restoration model is required to remove haze from distorted images. However, the design of visibility restoration models is an ill-posed problem as the physical information, such as depth information and attenuation model, is usually unknown. The physical parameters computed using existing models, such as dark channel prior and gradient channel prior, are not accurate, especially for images with large haze gradients. Therefore, in this article, an evolving visibility restoration model is proposed for remote sensing images. Initially, the fusion-based transmission map is computed from the foreground and sky regions. The transmission map is further improved by designing a hybrid constraint-based variational model. Finally, a dynamic differential evolution is utilized to optimize the control parameters of the proposed model. The proposed model is validated on 50 synthetic benchmarks and 50 real-life remote sensing images. For comparative analysis, ten well-known restoration models are also considered. The comparative analysis demonstrates that the proposed model outperforms the existing restoration models.

Review on Panoramic Imaging and Its Applications in Scene Understanding

With the rapid development of high-speed communication and artificial intelligence technologies, human perception of real-world scenes is no longer limited to the use of small Field of View (FoV) and low-dimensional scene detection devices. Panoramic imaging emerges as the next generation of innovative intelligent instruments for environmental perception and measurement. However, while satisfying the need for large-FoV photographic imaging, panoramic imaging instruments are expected to have high resolution, no blind area, miniaturization, and multidimensional intelligent perception, and can be combined with artificial intelligence methods towards the next generation of intelligent instruments, enabling deeper understanding and more holistic perception of 360° real-world surrounding environments. Fortunately, recent advances in freeform surfaces, thin-plate optics, and metasurfaces provide innovative approaches to address human perception of the environment, offering promising ideas beyond conventional optical imaging. In this review, we begin with introducing the basic principles of panoramic imaging systems, and then describe the architectures, features, and functions of various panoramic imaging systems. Afterwards, we discuss in detail the broad application prospects and great design potential of freeform surfaces, thin-plate optics, and metasurfaces in panoramic imaging. We then provide a detailed analysis on how these techniques can help enhance the performance of panoramic imaging systems. We further offer a detailed analysis of applications of panoramic imaging in scene understanding for autonomous driving and robotics, spanning panoramic semantic image segmentation, panoramic depth estimation, panoramic visual localization, and so on. Finally, we cast a perspective on future potential and research directions for panoramic imaging instruments.

Design and Characterization of Self-Shielded MRI Gradient Coils With Finite Track Width

Gradient coils are essential for the performance of the MR imaging system. Usually, coils are designed assuming thin wire tracks. Here, we design an MR gradient coil set using a more general approach considering the exact track width using the discrete wire approach. The effect of track width on the DC current density distribution and resultant magnetic fields using both loop and Golay coils are first demonstrated. Both, self-shielded X and Z gradient coils of definite width/thickness are designed and optimized. The resistance and inductance of the coils are calculated using the stream functions approach. Track current distribution was used to compute the magnetic fields over the desired volume, and at the cryostat. The linearity of the magnetic field over the volume, the figure of power, and the shielding ratio of the coil are used as parameters in the optimization process. The DC characteristics of the designed coils with definite (small) track width and thickness were compared for verification to that of the corresponding thin wire design where they were found to have approximately similar characteristics. Using our design methodology, the coils’ frequency-dependent resistances and inductances were directly/efficiently calculated. The harmonic and transient eddy current interactions between the longitudinal and transverse gradient coils were computed where track slitting was employed to reduce such interactions. This work stresses the importance of considering coil track width in the design process particularly for wide tracks as well as computing the coil’s figure of merit, harmonic and transient coil characteristics/interactions.

Assessing the performance of ultrasound imaging systems using images from relatively high-density random spherical void phantoms: A simulation study.

The development of clinically meaningful, objective, and quantitative methods for assessing the performance of ultrasound imaging systems represents a continuing area of interest. One approach has been to image phantoms with randomly distributed spherical voids. The objectives of this study were: (1) to explore the potential of using relatively high-volume fraction random spherical void (RSV) phantoms as an approach for quantitatively assessing the performance of ultrasound imaging systems; (2) to identify potential metrics that can be used to provide quantitative assessments of images obtained from relatively high-volume fraction RSV phantoms; and (3) to demonstrate changes in the quantitative metrics that can occur as image features are degraded. A series (10 each) of computer-simulated RSV phantoms with a range of RSV volume fractions (0.05, 0.15, and 0.25) were generated. To determine the number of image planes necessary to provide robust measurements, a series of consecutive planes (ranging from 1 to 150) within each type of simulated phantom were analyzed. The observed circular cross-section radii histogram distributions (representing the intersection of each plane with the local distribution of spherical voids) were compared with the theoretical histogram distribution. Simulated phantom images were produced by adding speckle and degradation of imaging system performance was modeled by averaging 1 to 9 neighboring planes to represent increasing elevation plane thicknesses. Quantification of the performance of the imaging system was determined by measuring the: (1) mean number of circular cross-sections detected per image frame; (2) mean fractional area of circular cross-sections detected per image frame; (3) agreement of observed circular cross-section radii histogram distribution with the theoretical distribution (Chi-square statistic); and (4) contrast and contrast-to-noise ratio as a function of observed circular cross-section radius. Results suggest that analyses of a sufficient number of image planes (providing over approximately 3000 total circular cross-sectional areas) provides excellent agreement between the observed and theoretical histogram distributions (mean Chi-square<0.004). For the 0.15 volume fraction series of simulated RSV phantoms, using 150 image plane analyses, phantom images show decreasing mean number of circle cross-sections detected per frame (31.5 ± 0.3, 28.4 ± 0.3, 28.2 ± 0.3, 26.3 ± 0.3, and 25.3 ± 0.3); decreasing mean fractional area of circle cross-sections per frame (0.157 ± 0.002, 0.133 ± 0.001, 0.133 ± 0.001, 0.111 ± 0.001, and 0.108 ± 0.001); and a decreasing agreement with the theoretical histogram distribution of radii (Chi-square values: 0.070 ± 0.004, 0.140 ± 0.005, 0.149 ± 0.007, 0.379 ± 0.011, and 0.518 ± 0.010) for 1, 3, 5, 7, and 9 plane averages, respectively. Contrast and contrast-to-noise measurements as a function of observed circular cross-section radius also demonstrate marked changes with simulated image degradation. Results of this simulation study suggest that analyses of images obtained from relatively high-density RSV phantoms may offer a promising approach for assessing ultrasound imaging systems. The proposed measurements appear to provide reproducible, robust, quantitative metrics that can be compared with corresponding theoretical values to provide quantifiable, objective metrics of imaging system performance.