Acquisition Of High-quality Images Research Articles

Non-systematic noise reduction framework for ToF camera

Time-of-flight (ToF) cameras enable a diverse range of applications due to their high frame rate, high resolution, and low cost. However, these cameras suffer from non-systematic noise during the acquisition of high-quality depth images, severely affecting their range accuracy. In this paper, we propose a non-systematic noise reduction framework named “DCS2Noise” to address this issue. This framework comprises a three-stage denoising strategy, involving noise standardization, deep learning-based differential correlation sampling (DCS) denoising and further enhancement with pairwise noise suppression. This framework directly captures and denoises DCS images during the ToF imaging process, making it more suitable for non-systematic noise reduction in ToF cameras. Compared to traditional methods, our approach significantly reduces the root mean squared error (RMSE) and improves the noise reduction ratio, peak signal to noise ratio (PSNR), and structural similarity index measure (SSIM). We believe that this study provides new insights into understanding noise in ToF cameras and offers effective references for reducing non-systematic noise in three-dimensional measuring instruments.

Clinical Implementation of Total-Body PET in China.

Total-body (TB) PET/CT is a groundbreaking tool that has brought about a revolution in both clinical application and scientific research. The transformative impact of TB PET/CT in the realms of clinical practice and scientific exploration has been steadily unfolding since its introduction in 2018, with implications for its implementation within the health care landscape of China. TB PET/CT's exceptional sensitivity enables the acquisition of high-quality images in significantly reduced time frames. Clinical applications have underscored its effectiveness across various scenarios, emphasizing the capacity to personalize dosage, scan duration, and image quality to optimize patient outcomes. TB PET/CT's ability to perform dynamic scans with high temporal and spatial resolution and to perform parametric imaging facilitates the exploration of radiotracer biodistribution and kinetic parameters throughout the body. The comprehensive TB coverage offers opportunities to study interconnections among organs, enhancing our understanding of human physiology and pathology. These insights have the potential to benefit applications requiring holistic TB assessments. The standard topics outlined in The Journal of Nuclear Medicine were used to categorized the reviewed articles into 3 sections: current clinical applications, scan protocol design, and advanced topics. This article delves into the bottleneck that impedes the full use of TB PET in China, accompanied by suggested solutions.

Mid-infrared Imaging Using Strain-Relaxed Ge1-xSnx Alloys Grown on 20 nm Ge Nanowires.

Germanium-tin (Ge1-xSnx) semiconductors are a front-runner platform for compact mid-infrared devices due to their tunable narrow bandgap and compatibility with silicon processing. However, their large lattice parameter has been a major hurdle, limiting the quality of epitaxial layers grown on silicon or germanium substrates. Herein, we demonstrate that 20 nm Ge nanowires (NWs) act as effective compliant substrates to grow extended defect-free Ge1-xSnx alloys with a composition uniformity over several micrometers along the NW growth axis without significant buildup of the compressive strain. Ge/Ge1-xSnx core/shell NWs with Sn content spanning the 6-18 at. % range are achieved and processed into photoconductors exhibiting a high signal-to-noise ratio at room temperature with a cutoff wavelength in the 2.0-3.9 μm range. The processed NW devices are integrated in an uncooled imaging setup enabling the acquisition of high-quality images under both broadband and laser illuminations at 1550 and 2330 nm without the lock-in amplifier technique.

(422) - Acquisition of High-Quality Pulmonary Ultrasound Images in the Heart Failure Clinic Following a Short Period of Training

(422) - Acquisition of High-Quality Pulmonary Ultrasound Images in the Heart Failure Clinic Following a Short Period of Training

Advanced visual components inspired by animal eyes

Abstract Artificial vision systems pervade our daily lives as a foremost sensing apparatus in various digital technologies, from smartphones to autonomous cars and robotics. The broad range of applications for conventional vision systems requires facile adaptation under extreme and dynamic visual environments. However, these current needs have complicated individual visual components for high-quality image acquisition and processing, which indeed leads to a decline in efficiency in the overall system. Here, we review recent advancements in visual components for high-performance visual processing based on strategies of biological eyes that execute diverse imaging functionalities and sophisticated visual processes with simple and concise ocular structures. This review first covers the structures and functions of biological eyes (i.e., single-lens eyes and compound eyes), which contain micro-optic components and nanophotonic structures. After that, we focus on their inspirations in imaging optics/photonics, light-trapping and filtering components, and retinomorphic devices. We discuss the remaining challenges and notable biological structures waiting to be implemented.

Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition.

Hyperpolarized (HP) xenon magnetic resonance imaging (129Xe MRI) is a recently federal drug administration (FDA)-approved imaging modality that produces high-resolution images of an inhaled breath of xenon gas for investigation of lung function. However, implementing 129Xe MRI is uniquely challenging as it requires specialized hardware and equipment for hyperpolarization, procurement of xenon imaging coils and coil software, development and compilation of multinuclear MR imaging sequences, and reconstruction/analysis of acquired data. Without proper expertise, these tasks can be daunting, and failure to acquire high-quality images can befrustrating, and expensive. Here, we present some quality control (QC) protocols, troubleshooting practices, and helpful tools for129Xe MRI sites, which may aid in the acquisition of optimized, high-quality data and accurate results. The discussion will begin with an overview of the process for implementing HP 129Xe MRI, including requirements for a hyperpolarizer lab, the combination of 129Xe MRI coil hardware/software, data acquisition and sequence considerations, data structures, k-space and image properties, and measured signal and noise characteristics. Within each of these necessary steps lies opportunities for errors, challenges, and unfavorable occurrences leading to poor image quality or failed imaging, and this presentation aims to address some of the more commonly encountered issues. In particular, identification and characterization of anomalous noise patterns in acquired data are necessary to avoid image artifacts and low-quality images; examples will be given, and mitigation strategies will be discussed. We aim to make the 129Xe MRI implementation process easier for new sites while providing some guidelines and strategies for real-time troubleshooting.

The Colourimetric Method for Mixing Time Measurement in Single-Use and Multi-Use Bioreactors—Methodology Overview and Practical Recommendations

Mixing time is an important parameter for quantifying the mixing efficiency of a bioreactor system, essential for successful bioprocess development in various branches of the bioengineering sector (e.g., biopharma, biorefineries, food industry and bioreactor design). The colourimetric method is one of the ways of obtaining valuable quantitative data about the mixing process and the liquid flow inside a vessel. This review consists of a catalogue and a discussion of previously published data in which the colourimetric method has been utilised; a critical comparison between the colourimetric and other mixing time measurement methods; an explanation of practical considerations regarding the bioreactor setup and the choice of reagents; a practical guide for requirements for the acquisition of high-quality images of the mixing process; a thorough discussion of aspects connected to the computer image processing of the video material. This review is intended to thoroughly present the versatility of the colourimetric method for mixing time measurement in miscellaneous bioreactor systems, i.e., in classical tanks and modern single-use (disposable) plastic film-based bag-like containers, and to facilitate the implementation of the colourimetric method in new research setups by providing complete and valuable recommendations about each step of the methodology.

High-speed k-linear swept laser using acousto-optic deflectors with Doppler shift compensation for optical coherence tomography.

Swept laser based on the acousto-optic deflector (AOD) is a promising swept source in optical coherence tomography (OCT) applications for its high wavenumber linear sweep without mechanical motion. However, the poor coherence length and the elongated cavity of the laser imposed limitations on the acquisition of high-quality images with adequate imaging depth and high imaging speed. In this Letter, we demonstrate a compact high-speed wavenumber linear swept laser based on AOD using Doppler shift compensation, achieving a high linearity of Pearson's R of 0.999991, a duty cycle of ∼100%, an extended coherence length of 5.7 mm, an output power of 18 mW, and excellent phase stability at a sweep speed of 500 kHz. OCT structural images with a system sensitivity of 103.2 dB and OCT angiography (OCTA) of human palm in vivo have been successfully performed, serving as a compelling demonstration of the excellent performance of this swept laser. We believe that the proposed laser will be of high potential in various clinical and industrial applications in the future.

H2 molecular gas in the old planetary nebula NGC 3587

ABSTRACT The acquisition of high-quality deep images of planetary nebulae (PNe) has allowed the detection of a wealth of small-scale features, which highlight the complexity of the formation history and physical processes shaping PNe. Here we present the discovery of three groups of clumps embedded within the nebular shell of the evolved PN NGC 3587, the Owl Nebula, that had escaped previous detections. The analysis of multi-wavelength GEMINI GMOS, NOT ALFOSC, Aristarchos Andor optical, Canada–France–Hawaii Telescope WIRCam, and Spitzer IRAC and MIPS infrared images indicates that these clumps are formed by material denser and colder than the surrounding nebula, with a notable content of molecular H2, but negligible or null amounts of dust. The presence of H2-rich pockets embedded within the ionized shell of this evolved PN is suggestive of the survival of high-density condensations of material created at the onset of the PN stage.

Semi-Supervised Standard-Dose PET Image Generation via Region-Adaptive Normalization and Structural Consistency Constraint.

Positron Emission Tomography (PET) is an important nuclear medical imaging technique, and has been widely used in clinical applications, e.g., tumor detection and brain disease diagnosis. As PET imaging could put patients at risk of radiation, the acquisition of high-quality PET images with standard-dose tracers should be cautious. However, if dose is reduced in PET acquisition, the imaging quality could become worse and thus may not meet clinical requirement. To safely reduce the tracer dose and also maintain high quality of PET imaging, we propose a novel and effective approach to estimate high-quality Standard-dose PET (SPET) images from Low-dose PET (LPET) images. Specifically, to fully utilize both the rare paired and the abundant unpaired LPET and SPET images, we propose a semi-supervised framework for network training. Meanwhile, based on this framework, we further design a Region-adaptive Normalization (RN) and a structural consistency constraint to track the task-specific challenges. RN performs region-specific normalization in different regions of each PET image to suppress negative impact of large intensity variation across different regions, while the structural consistency constraint maintains structural details during the generation of SPET images from LPET images. Experiments on real human chest-abdomen PET images demonstrate that our proposed approach achieves state-of-the-art performance quantitatively and qualitatively.

High-quality TEM specimen preparation for lithium-ion conducting solid electrolytes by low-energy ion milling

Focused ion beam (FIB) is a widely used method to prepare transmission electron microscopy (TEM) specimen from bulk materials. However, the surface amorphous layer induced by ion beam is an obstacle to obtain high-quality atomic-scale images for quantitative analysis, especially for the analysis of light elements such as lithium in lithium-ion conducting solid electrolytes. Here, taking lithium-ion conducting solid electrolyte materials as an example, the advantages and disadvantages of applying low-energy Ar+ ion for fine milling after FIB are investigated. Combining Monte-Carlo simulations with ion milling experiments, the milling parameters are evaluated and discussed in detail. With optimized parameters, TEM specimens with less beam damage and thinner amorphous layer were prepared, enabling the acquisition of high-quality atomic-scale images. Furthermore, low-energy Ar+ ion milling is also able to remove hydrocarbon contamination formed during the electron beam illumination inside the microscope, making the contaminated TEM specimens reusable.

Fabrication of a multifaceted mapping mirror using two-photon polymerization for a snapshot image mapping spectrometer.

A design and fabrication technique for making high-precision and large-format multifaceted mapping mirrors is presented. The method is based on two-photon polymerization, which allows more flexibility in the mapping mirror design. The mirror fabricated in this paper consists of 36 2D tilted square pixels, instead of the continuous facet design used in diamond cutting. The paper presents a detailed discussion of the fabrication parameters and optimization process, with particular emphasis on the optimization of stitching defects by compensating for the overall tilt angle and reducing the printing field of view. The fabricated mirrors were coated with a thin layer of aluminum (93nm) using sputter coating to enhance the reflection rate over the target wave range. The mapping mirror was characterized using a white light interferometer and a scanning electron microscope, which demonstrates its optical quality surface (with a surface roughness of 12nm) and high-precision tilt angles (with an average of 2.03% deviation). Finally, the incorporation of one of the 3D printed mapping mirrors into an image mapping spectrometer prototype allowed for the acquisition of high-quality images of the USAF resolution target and bovine pulmonary artery endothelial cells stained with three fluorescent dyes, demonstrating the potential of this technology for practical applications.

Full-Coverage Path Planning and Stable Interaction Control for Automated Robotic Breast Ultrasound Scanning

Ultrasound examination is widely used for diagnosis of breast cancer, which requires a full-coverage scan of the whole organ and stable probe–breast interaction for high-quality image acquisition. In this study, a robotic system for automated breast ultrasound scanning is proposed. To avoid occlusion, point cloud of the breast is obtained from multiple angles and registered together for accurate tissue shape reconstruction, then scan path planning is performed with isometric 3-D point cloud searching algorithm for full and uniform coverage. To reduce the adverse influence of large tissue deformation during ultrasound scanning, a contact force–strain regression model is built for tissue deformation estimation and used as a feedforward to correct the planned scanning path, and a probe–tissue interaction model with scanning resistance is built for normal probe orientation adjustment. To maintain normal probe orientation and stable contact force during robotic ultrasound scanning, a hybrid force–velocity control framework is proposed based on admittance control algorithm. Experiment results show that the robotic system can successfully maintain a constant contact force and keep the probe's posture along the normal orientation of probe–breast interaction both in in-plane direction and out-of-plane direction.

Polarization image demosaicing and RGB image enhancement for a color polarization sparse focal plane array.

The color division of focal plane (DoFP) polarization sensor structure mostly uses Bayer filter and polarization filter superimposed on each other, which makes the polarization imaging unsatisfactory in terms of photon transmission rate and information fidelity. In order to obtain high-resolution polarization images and high-quality RGB images simultaneously, we simulate a sparse division of focal plane polarization sensor structure, and seek a sweet spot of the simultaneous distribution of the Bayer filter and the polarization filters to obtain both high-resolution polarization images and high-quality RGB images. In addition, From the perspective of sparse polarization sensor imaging, leaving aside the traditional idea of polarization intensity interpolation, we propose a new sparse Stokes vector completion method, in which the network structure avoids the introduction and amplification of noise during polarization information acquisition by mapping the S1 and S2 components directly. The sparsely polarimetric image demosaicing (Sparse-PDM) model is a progressive combined structure of RGB image artifact removal enhancement network and sparsely polarimetric image completion network, which aims to compensate sparsely polarimetric Stokes parameter images with the de-artifacts RGB image as a guide, thus achieving high-quality polarization information and RGB image acquisition. Qualitative and quantitative experimental results on both self-constructed and publicly available datasets prove the superiority of our method over state-of-the-art methods.

A Novel CS 2G-starlet denoising method for high noise astronomical image

In deep space exploration, astronomical images are easily contaminated by noise, which affects image quality. However, for the denoising of high-noise astronomical images, obtaining good reconstruction results from the current denoising methods is difficult. This paper proposes a novel compressed sensing (CS) 2G-starlet denoising (NCSSD) method can effectively improve the reconstruction quality of astronomical images. Firstly, the proposed 2G-starlet Wiener filtering operator is used to select these starlet coefficients in the process of sparse image transformation. Then, a novel iterative stepsize operator is proposed to enhance the convergence ability of the algorithm. At the same time, an optimized cycle spinning method is proposed to adjust the reconstructed image. Through extensive simulation experiments and deep theoretical analysis and verification, the effectiveness of this method in high-noise astronomical image denoising is fully proven, and the quality of reconstructed image is improved. The proposed method has been successfully interconnected with the telescope and industrial camera, realizing the rapid acquisition of high-quality astronomical images. The research results of this article have important value for promoting the effective acquisition and analysis of astronomical images in exploring deep space.

Troubleshooting FoCUS Image Acquisition: Patient Positioning, Transducer Manipulation, and Image Optimization

Focused cardiac ultrasound (FoCUS) is a limited, clinician-performed application of echocardiography to add real-time information to patient care. These bedside exams are problem oriented, rapidly and repeatedly performed, and largely qualitative in nature. Competency in FoCUS includes mastery of the stereotactic and psychomotor skills required for transducer manipulation and image acquisition. Competency also requires the ability to optimize the setup, troubleshoot image acquisition, and understand the sonographic limitations because of complex clinical environments and patient pathology. This article presents concepts for successful, high-quality two-dimensional (B-mode) image acquisition in FoCUS. Concepts of high-quality image acquisition can be applied to all established sonographic windows of the FoCUS exam: the parasternal long-axis (PLAX), parasternal short-axis (PSAX), apical four chamber (A4C), subcostal fourchamber (SC4C), and the inferior vena cava (IVC). The apical five-chamber (A5C) and subcostal short-axis (SCSA) views are mentioned, but are not discussed in-depth. A pragmatic figure illustrating the movements of the phased array transducer is also provided to serve as a cognitive aid during FoCUS image acquisition.

Project-Oriented RF Coil Comparison and Optimization for Preclinical, Single-Voxel MR Spectroscopy of the Rat Visual Cortex at 9.4 T

As one of the most important cortical structures in the brain, the visual cortex plays a primary role in processing visual data. Observing the metabolic changes in this region using single-voxel MR spectroscopy (MRS) can provide a plethora of information on the disease stage and progress in vivo. For single-voxel MRS experiments, a target voxel is always chosen and specifically investigated. The volume of the voxel must be sufficiently small to avoid any interference from adjacent areas but large enough to maximise its signal-to-noise ratio (SNR). Of the factors used to improve SNR, e.g. enlarging voxel size or increasing the number of signal averaging, the optimisation of the RF coil can contribute significantly to the SNR improvement. In this work, we compared and optimised RF coils which include a circularly-polarised (CP) high-pass birdcage coil and two CP surface coils with different dimensions. The coils were particularly designed for the entire rat head, brain and the target region (visual cortex), respectively. The performance of these coils was evaluated based on the project-specific purpose of investigating metabolite concentration changes in the visual cortex of the in vivo rat brain, assessed by means of single-voxel MRS at 9.4 T. In the SNR comparison, the values obtained using the optimised small loop coil were found to be approximately 5 and 1.35 times higher than those using the birdcage volume head coil and the medium-sized loop coil, respectively. In other words, using the optimised coil rather than, for example, the birdcage coil allows the acquisition to be completed more quickly by a factor of 25 times. In conclusion, by using the optimised setup, we can i) benefit either from reduced measurement time or in the acquisition of high-quality MR images or ii) obtain spectra with a minimum quantification error.

G-ROBOT: An Intelligent Greenhouse Seedling Height Inspection Robot

An intelligent and modular greenhouse seedling height inspection robot was designed to meet the demand for high-throughput, low-cost, and nondestructive inspection during the growth of greenhouse seedlings. The robot structure mainly consists of a multiterrain replacement chassis, an electronic control lift image acquisition support, and a quick disassembly mechanism. SolidWorks was used to design the robot and Adams was used for motion simulations. Based on STM32 and Raspberry Pi as the core, the robot is equipped with various sensors to build a reliable control system for intelligent navigation for inspection tasks as well as acquisition of high-quality images and environmental information data of seedling crops. The developed growth point detection algorithm based on the EfficientNet deep learning network can efficiently measure the heights of seedlings and the application of the host software and cloud server makes it easy to monitor and control the robot and store and manage various data. The results of the greenhouse experiment showed that the robot has an average battery life of 5.2 h after being fully charged, with satisfactory motion stability and environmental adaptability; the environmental information data collected were valid, and errors were within the acceptable range; the captured seedling crop images were of high quality, and the seedling height data obtained through algorithm analysis were valid and reliable. The robot is expected to be an intelligent assistant for seedling research and production.

Automatic bone segmentation for oral surgical planning

Introduction: Evolvement of digital technology encouraged the use of virtual dental and dental surgical planning and navigated surgery. The variety of cases is significant, therefore even for an expert, it is challanging to recover a traumatic case, or to design and apply implants with high anatomical precision. Objective: High-quality image acquisition and processing are essential to the process. CT (computer tomography) or CBCT (cone-beam computer tomography) images having bad initial quality greatly decrease the performance of the processing algorithms and affect the quality of the reconstructed 3D models. 3D reconstruction using manual segmentation takes several hours of work and expertise, which significantly increases the overall cost and time of 3D CAD/CAM (computer-aided design/computer-aided manufacturing) based surgical planning and production processes. Material and method: In this paper, we introduce a bone segmentation algorithm specifically designed for surgical planning, and evaluate its benefits for the aforementioned goal. The approach relies on edge detection, mathematical morphology and basic image-processing operations. Results: Performance has been evaluated on 40 series of manual segmentation. Results (precision 90%) show that the algorithm is fast and accurate so it is applicable for surgical planning. Conclusion: Our algorithm significantly reduces the execution time of segmentation and surgical planning, therefore increases the efficiency of the overall procedure.

Automatic Measurement of External Thread at the End of Sucker Rod Based on Machine Vision.

Aiming at the low efficiency of manual measurement of threads and the lack of practicability in machine vision measurement before, online size measurement of threads at the end of sucker rods based on machine vision was studied. A robotic arm is used to carry an optical device to achieve high-quality image acquisition of threads. Based on the prior knowledge of the thread profile angle, the directional edge detection operator is customized to achieve the accurate detection of the left and right edges of the thread. Noise filtering, sorting, and left and right edge-matching algorithms based on connected domains are developed to eliminate the interference effects of electrostatic dust and oil pollution in online measurement, and the dimension of thread profile angles, pitches, major diameters, and minor diameters can be precisely calculated. The experimental results show that the screw thread parameter measurement time is about 0.13 s; the maximum and minimum average errors of the thread angles are 0.011° and 0.632°, respectively; and the total average deviation is less than 0.08°. For the screw thread pitch, major diameter, minor diameter, and pitch diameter parameter measurement, the deviation of the measurement results between the proposed method and the universal tool microscope (UTM) method is less than 10 μm. It fully proves the effectiveness and accuracy of the method in this paper and, at the same time, shows that the method has good real-time performance and high application significance, which lays a good foundation for the subsequent online thread measurement.