Large Field Of View Research Articles

Large-field high-resolution X-ray AKB microscope for measuring hydrodynamic instabilities at the SG-III prototype laser facility.

X-ray imaging with a large field of view (FOV) and high resolution is extremely important for Rayleigh-Taylor instability measurement with a small amplitude and high spatial frequency in laser inertial confinement fusion. We developed an advanced Kirkpatrick-Baez (AKB) microscope based on the quadratic-aberration theory to realize a large FOV and high resolution. This microscope was assembled and tested in a laboratory, and it was then successfully applied for imaging the hydrodynamic instability of a perturbation target in implosion experiments at the Shenguang-III prototype laser facility. Imaging results demonstrate that the AKB microscope can achieve an optimal resolution of ~ 0.53μm and ~ 0.40μm and a spatial resolution of < 1.5μm within a 300-µm FOV and < 4.5μm in a 1-mm FOV.

Decoding Continuous Tracking Eye Movements from Cortical Spiking Activity.

Eye movements are the primary way primates interact with the world. Understanding how the brain controls the eyes is therefore crucial for improving human health and designing visual rehabilitation devices. However, brain activity is challenging to decipher. Here, we leveraged machine learning algorithms to reconstruct tracking eye movements from high-resolution neuronal recordings. We found that continuous eye position could be decoded with high accuracy using spiking data from only a few dozen cortical neurons. We tested eight decoders and found that neural network models yielded the highest decoding accuracy. Simpler models performed well above chance with a substantial reduction in training time. We measured the impact of data quantity (e.g. number of neurons) and data format (e.g. bin width) on training time, inference time, and generalizability. Training models with more input data improved performance, as expected, but the format of the behavioral output was critical for emphasizing or omitting specific oculomotor events. Our results provide the first demonstration, to our knowledge, of continuously decoded eye movements across a large field of view. Our comprehensive investigation of predictive power and computational efficiency for common decoder architectures provides a much-needed foundation for future work on real-time gaze-tracking devices.

Half-wavelength-pitch silicon optical phased array with a 180° field of view, high sidelobe suppression ratio, and complex-pattern beamforming

Solid-state optical beam steering devices desire a large field of view (FOV), good beam quality, and reconfigurable beamforming of complex patterns, which are not available in a single system yet. Having not been demonstrated, an active beamformer using an optical phased array (OPA) could potentially fulfill these requirements simultaneously, because it can control both the wavefront and beam pattern. Half-wavelength-pitch OPAs theoretically can achieve the three requirements concurrently, but suffer from crosstalk. Most previous efforts focus on mitigating/avoiding crosstalk. Instead, here we appreciate its existence and propose/demonstrate a programmable architecture to compensate for it. Using a tree of composite variable splitters with a full splitting-ratio range, we achieve arbitrary amplitude/phase modulation to pre-correct scrambled phase/amplitude by crosstalk. With comprehensive stray-light minimization strategies, the sidelobe suppression ratio (SLSR) is significantly improved. Our design achieves a 180∘ FOV, a peak SLSR of 24 dB, and complex-pattern beamforming simultaneously in a half-wavelength-pitch 64-waveguide array. Within the ±60∘ range, a SLSR of &gt;20dB is achieved. Our OPA demonstrates Bayliss difference, pulse-shaped, and asymmetric three-beam patterns with high SLSRs of &gt;20dB, ∼10dB, and &gt;18dB, respectively. These performance metrics are important for various applications in light detection and ranging, imaging, and communication.

112° field of view high-resolution swept-source OCT angiography for rat retinas.

This study introduces an ultra-wide field (UWF) and high-resolution swept-source optical coherence tomographic angiography (OCTA) system for rat retinal imaging. Using an asymmetrical optics design, the system achieves unprecedented details of retinal structures and vascular plexuses over a large field of view (112°) in a single-shot acquisition. Views of single-nerve fiber bundles and single capillary vessels are consistently visible over a 112° field of view. The system has a long imaging range and high penetration and allows a full view of vitreous hyaloid vessels, retina, choroid, sclera, and posterior ciliary arteries, down to sub-sclera connective tissues. In a longitudinal study of oxygen-induced retinopathy (OIR) in rats, the system successfully revealed the progression and regression of OIR-related vascular pathologies, such as ischemia, neovascularization, and tortuosity. To our knowledge, this novel UWF-OCT/OCTA prototype designed for rat retinal imaging will be a vital tool for monitoring disease progression and evaluating therapeutic interventions in preclinical models.

Research on single-point fast three-dimensional concentration reconstruction of a smoke plume based on the static interference infrared imaging spectroscopy system

To meet the requirements of real-time and effectiveness of three-dimensional concentration telemetry of gas clouds and address the difficulty of fast three-dimensional concentration reconstruction of single instrument smoke plumes, the paper proposes a single-point fast three-dimensional concentration reconstruction of the smoke plume based on a static interference infrared Fourier transform imaging spectrometer (ISIFTS) by using the advantages of high throughput, large field of view, high stability, and rapid detection. Based on the scanning field switching characteristics of ISIFTS, a single instrument quickly scans the dual-field map data to obtain the three-dimensional point cloud of the target scene. Combined with the three-dimensional spatial parameters of the scene, a multi-dimensional re-projection algorithm is constructed based on the Gaussian plume continuous diffusion model to simulate the concentration-path-length product (CL) image, and the measured CL image is solved by analyzing the smoke plume image spectra data. The normalized cross-correlation fitting algorithm is used to perform the optimal matching of simulated-measured CL images, and then the three-dimensional concentration distribution of the plume scene is reconstructed based on the dimension mapping relationship. The field smoke plume telemetry experiment was designed and carried out, and the three-dimensional concentration distribution of plume gas at three emission points in the scene was obtained. The CO2 emission rates were calculated to be 13.572 kg / s, 12.225 kg / s, and 14.114 kg / s, respectively. The data are consistent with the emission rate of the coal-fired thermal power plant, which verifies the effectiveness of the single-point fast three-dimensional concentration reconstruction of the smoke plume method based on the ISIFTS system.

Mesoscopic axially swept oblique plane microscope for the imaging of freely moving organisms with near-isotropic resolution

Rapid three-dimensional imaging over extended fields of view (FOVs) is crucial to the study of organism-wide systems and biological processes in vivo. Selective-plane illumination microscopy (SPIM) is a powerful method for high spatio-temporal resolution in toto imaging of such biological specimens. However, typical SPIM implementations preclude conventional sample mounting and have anisotropic imaging performance, in particular when designed for large FOVs over 1 mm diameter. Here, we introduce axial sweeping of the illumination into a non-orthogonal dual-objective oblique plane microscope (OPM) design, thereby enabling the observation of freely moving animals over millimeter-sized FOVs, at close to isotropic, sub-cellular resolution. We apply our mesoscopic axially swept OPM (MASOPM) to image the behavioral dynamics of the sea anemone Nematostella vectensis over 1 × 0.7 × 0.4 mm at 1.7 × 2.6 × 3.7 µm resolution and 0.5 Hz volume rate.

Evaluation of a novel forward-looking optical coherence tomography probe for endoscopic applications: an ex vivo feasibility study.

As a result of recent advances in the development of small microelectromechanical system mirrors, a novel forward-looking optical coherence tomography (OCT) probe with a uniquely large field of view is being commercially developed. The aim of this study is to prospectively assess the feasibility of this advanced OCT probe in interpreting ex vivo images of colorectal polyp tissue and to identify necessary steps for further development. A total of 13 colorectal lesions from 9 patients, removed during endoscopic resection, were imaged ex vivo with the OCT device and compared with histopathological images that served as the gold standard for diagnostics. Normal tissue from one patient, removed during the endoscopic procedure, was imaged as a negative control. We assessed the presence of features indicative for polyp type and degree of dysplasia, by comparing OCT images to histopathological images and by evaluating the presence of OCT-specific features identified by previous studies, such as effacement (loss of layered tissue structure), a hyperreflective epithelial layer, and irregularity of the surface. As verified by corresponding histological images, tissue structures such as blood vessels and tissue layers could be distinguished in OCT images of the normal tissue sample. Detailed structures on histological images such as crypts and cell nuclei could not be identified in the OCT images. However, we did identify OCT features specific for colorectal lesions, such as effacement and a hyperreflective epithelial layer. In general, the imaging depth was about 1mm. Some relevant tissue structures could be observed in OCT images of the novel device. However, some adaptations, such as increasing imaging depth using a laser with a longer central wavelength, are required to improve its clinical value for the imaging of colorectal lesions.

Dual-biomimetic curved compound-eye camera system for multi-target distance measurement in a large field of view

Biomimetic curved compound-eye cameras (BCCECs) have attracted great attention for their potential applications in a variety of fields such as target recognition, monitor and three-dimensional localization in military due to their unique optical properties such as large field of view (FOV) and small size. In this work, we proposed a multi-target distance measurement method based on a dual-BCCEC system in a large FOV. To guarantee the precise measurement of the distance of multiple targets, a feature point searching and matching algorithm is developed for the dual-BCCEC system to improve the localizing efficiency of common feature points. In addition, a CALibration Tag (CALTag) self-recognition calibration method is also developed to calibrate ommatidia of the BCCEC with a high efficiency. Based on these two methods, the coordinates of multiple targets with clear feature points can be obtained after the distortion correction in sub-images and thus the distances of multiple targets with clear feature points can be achieved simultaneously with a single compound-eye raw image. The experiment results show that the dual-BCCEC system has a high distant measurement accuracy with an error of less than 6.80% for at least ten different targets in the a working distance ranging from 400 to 600 m in a quite large FOV of 98°×98°. The method demonstrated in this work can pave the way for multi-targets tracking in those related areas with high security monitoring requirements.

Minimizing prostate diffusion weighted MRI examination time through deep learning reconstruction

PurposeTo study the diagnostic image quality of high b-value diffusion weighted images (DWI) derived from standard and variably reduced datasets reconstructed with a commercially available deep learning reconstruction (DLR) algorithm. Materials and methodsThis was a retrospective study of 52 patients undergoing conventional prostate MRI with raw image data reconstructed using both conventional 2D Cartesian and DLR algorithms. Simulated shortened DWI acquisition times were performed by reconstructing images using DLR datasets harboring a reduced number of excitations (NEX). Two radiologists independently evaluated the image quality using a 4-point Likert scale. Signal-to-noise ratio (SNR) analysis was performed for the entire cohort and a subset of patients identified as having clinically significant prostate cancer identified at MRI, and later confirmed by pathology. ResultsRadiologists perceived less image noise for both restricted and large field of view (FOV) standard NEX dataset DLR diffusion images compared to conventionally reconstructed images with good interreader agreement. Diagnostic image quality was maintained for all DLR images using variably reduced NEX compared to conventionally reconstructed images employing the standard NEX. Improved signal to noise was observed for the restricted FOV DLR images compared to conventional reconstruction using standard NEX. DLR diffusion images derived from reduced NEX datasets translated to time reductions of up to 68 % and 39 % for the restricted and large FOV series acquisitions, respectively. ConclusionDLR of diffusion weighted images can reduce image noise at standard NEX and potentially reduce prostate MRI exam time when utilizing reduced NEX datasets without sacrificing diagnostic image quality.

Desensitization design of freeform off-axis TMA optical systems with configuration selection

The off-axis three-mirror anastigmatic (TMA) optical system has the advantages of eliminating all primary aberrations, having no aperture obscuration, no chromatic aberration, and good environmental adaptability, making it essential in high-performance optical instruments. Freeform surfaces, with their rich degrees of freedom (DOFs) in mathematical representation, positively affect the image quality and sensitivity of optical systems. When applied correctly to off-axis TMA optical systems, they can achieve fast F-numbers, large fields of view (FOVs), and long focal lengths. There are dozens of configurations for off-axis TMA optical systems, and freeform surfaces can be combined in numerous ways within these systems. This paper first analyzes the sensitivity of off-axis TMA optical systems with different configurations, selects the configuration with the lowest sensitivity, and combines it with a low sensitivity freeform surface combination to achieve high-performance freeform off-axis TMA optical systems with low sensitivity.

Label-free detection and simultaneous viability determination of CTCs by lens-free imaging cytometry.

The detection of extremely rare circulating tumor cells (CTCs) in peripheral blood and simultaneously identifying their viabilities are significant for cancer diagnosis and prognosis as well as monitoring the efficacy of personalized treatment. A lens-free imaging system features high-resolution images taken over a large field of view (FOV), which has great potential for CTC detection and viability determination. But current still lens-free systems restrict the application for CTC detection in real samples due to the inherent limitations of lens-free technology: (1) the location of cells in the FOV will affect the imaging; (2) the extremely rare CTCs probably did not exist in one observation. In this paper, we realized the detection of CTCs in whole blood and the simultaneous determination of their viabilities by lens-free imaging cytometry. Our in-flow system plus a large FOV range of lens-free imaging highly increased the detection rate of rare CTCs with a high throughput of 150,000 cells per minute and improved the recognition efficiency for blood cells, living/dead CTCs by using a cell tracing-assisted deep learning algorithm. With this method, the average precision of blood cells, living/dead lung cancer cells A549, and living/dead colon cancer cells SW620 reached 98.80%, 97.88%, 97.93%, 97.72%, and 98.60%, respectively. Our system got a highly consistent result with the manual counting method using fluorescent staining (Pearson's r 99.93% for SW620) and can easily detect as few as 10 dead or living CTCs from 100,000 white blood cells (WBCs). Finally, real clinical samples were detected in our system. Both dead and living CTCs were found in all six advanced-stage cancer patients, and the number of living CTCs per million WBCs ranged from 13 to 39, more than that of the dead CTCs (5 to 25), while none of the CTCs were detected in six healthy control subjects. Moreover, we also found that CTCs died very quickly after leaving the human body, indicating that CTCs should be studied as soon as possible after sampling. Although this method is implemented for CTCs, it can also be used for the detection of other rare cells.

Water-to-air unmanned aerial vehicle (UAV) based rolling shutter optical camera communication (OCC) system with gated recurrent unit neural network (GRU-NN)

Underwater sensors and autonomous underwater vehicles (AUVs) are widely adopted in oceanic research activities. As the number of underwater sensors and AUVs is growing quickly, the bandwidth requirements are increasing accordingly. In this work, we put forward and demonstrate a large field-of-view (FOV) water-to-air unmanned aerial vehicle (UAV) based optical camera communication (OCC) system with gated recurrent unit neural network (GRU-NN) for the first time to the best of our knowledge. As the UAVs are embedded with complementary-metal-oxide-semiconductor (CMOS) cameras, there is no need to install OCC receivers (Rxs), reducing the deployment cost. Moreover, the large photo-sensitive area of the CMOS camera can support a large FOV OCC transmission without the need for precise optical alignment. Here, by utilizing the column matrix identification during the rolling shutter pattern decoding in the CMOS image sensor, the scintillation caused by water turbulence can be reduced. Besides, in the outdoor and windy environment, the UAV will experience significant movement caused by the wind making it very difficult to capture stable OCC frames in the CMOS image sensor. Here, we propose and demonstrate utilizing GRU-NN, which is a special realization of the recurrent neural network (RNN) with memory cells capable of learning the time-domain dependent signals. It is shown that the GRU-NN can learn effectively from successive image frames in time-domain and produce correct prediction even under the windy and unstable UAV flying environment. Experimental results reveal that the proposed GRU-NN can outperform the previous pixel-per-symbol labeling neural network (PPS-NN), and also can significantly reduce the computation time when compared with long-short-term-memory-neural-network (LSTM-NN). The proposed system can decode 4-level pulse-amplitude-modulation (PAM4) rolling shutter OCC patterns at data rates of 5.4 kbit/s and 3.0 kbit/s under clear and cloudy water, respectively, fulfilling the pre-forward error correction bit-error rate (pre-FEC BER = 3.8 × 10−3). We also demonstrate that the UAV based OCC system can support data rates of 5.4 kbit/s, 4.2 kbit/s, and 3.0 kbit/s at distances of 2.2 m, 3.2 m, and 4.2 m, respectively, at outdoor and windy environments.

Multifunctional GAN-based optimization for X-ray tomography under different conditions

Based on the generative adversarial network (GAN), we present a multifunctional X-ray tomographic protocol for artifact correction, noise suppression, and super-resolution of reconstruction. The protocol mainly consists of a data preprocessing module and multifunctional GAN-based loss function simultaneously dealing with ring artifacts and super-resolution. The experimental protocol removes ring artifacts and improves the contrast-to-noise ratio (CNR) and spatial resolution (SR) of reconstructed images successfully, which shows the capability to adaptively rectify ring artifacts with varying intensities and types while achieving super-resolution. Compared with the main existing deep learning models or conventional tomographic correction methods, it also enables higher processing speed and minimal information loss, especially for images of smaller dimensions. This study provides a robust optimization tool for the equivalent realization of large fields of view and high-resolution X-ray tomography. The experimental datasets were collected from a series of X-ray cone-beam computed tomography scans of biological samples.

Off-axis freeform optical design for large curved field of view imaging

Recording neuron activities is pivotal for elucidating the functionality of the nervous system. However, the curved cortex surface of experimental mice presents a significant challenge for optical systems, particularly when a larger field of view (FOV) is required. To address this challenge, we have designed an off-axis three-mirror system that incorporates freeform surfaces on both the primary and secondary mirrors. This system achieves a large imaging FOV of 18°×9°, delivering near-diffraction-limit imaging quality across a curvature spectrum of −14.7 to −15.3mm. A manufacturability analysis indicates that the freeform surfaces are straightforward to produce, and the overall system demonstrates low sensitivity to tolerance and measurement errors. This study introduces a novel, to the best of our knowledge, solution to the field curvature constraints in optical imaging of cortical activity, providing substantial technical support for in vivo neuronal imaging endeavors.

Moving target detection based on multi-satellite joint passive microwave imaging

Using satellite formations to form a space-based passive interferometric imaging system can achieve high spatial resolution, but the sparse detection baseline will cause aliasing in the inversion image, affecting the detection of single-pixel point targets. Considering the slowly varying characteristics of the observation area, a target detection method based on image sequence is proposed. The background is estimated by multi-frame images, and the background of the inversion image is eliminated; energy is gathered based on sidelobe characteristics, the noise in the target area is estimated, and candidate targets are selected; the motion trajectory of the target is obtained by combining the temporal motion characteristics, and the detection of moving point targets is realized. Taking the formation system composed of 10 geostationary orbit satellites as an example, 300 simulation experiments are carried out for the detection of 50 ship point targets. The results show that the proposed method can realize point target detection in a large field of view, with an average false alarm rate 14.5%and an average missed alarm rate 19.5%.

Kilohertz volumetric imaging of in-vivo dynamics using squeezed light field microscopy.

Volumetric functional imaging of transient cellular signaling and motion dynamics poses a significant challenge to current microscopy techniques, primarily due to limitations in hardware bandwidth and the restricted photon budget within short exposure times. In response to this challenge, we present squeezed light field microscopy (SLIM), a computational imaging method that enables rapid detection of high-resolution three-dimensional (3D) light signals using only a single, low-format camera sensor area. SLIM pushes the boundaries of 3D optical microscopy, achieving over one thousand volumes per second across a large field of view of 550 μm in diameter and 300 μm in depth with a spatial resolution of 3.6 μm laterally and 6 μm axially. Using SLIM, we demonstrated blood cell velocimetry across the embryonic zebrafish brain and in a free-moving tail exhibiting high-frequency swinging motion. The millisecond temporal resolution also enables accurate voltage imaging of neural membrane potentials in the leech ganglion, and in the hippocampus of behaving mice. These results collectively establish SLIM as a versatile and robust imaging tool for high-speed microscopy applications.

Monte Carlo simulation study of the effect of thyroid shielding on radiation dose in dental cone beam CT in an adult male phantom.

In this paper, the effect of thyroid collars on radiation dose during dental cone-beam computed tomography (CBCT) was evaluated using Monte Carlo simulations and to calculate the effective dose underestimated for the actual CBCT examination due to accounting only for the head and neck. Three thyroid collar models that covered the surface of the phantom were established according to the International Commission on Radiological Protection (ICRP) adult-male mesh-type reference computational phantoms, and a Particle and Heavy Ion Transport code System was used to calculate the equivalent and effective doses of ICRP phantom when different thyroid shielding protocols were used in NewTom VGi evo CBCT, considering one medium (12×8cm) and one small (8×5cm) fields of view (FOVs), and two centre positions were used for each FOV. In four CBCT scanning scenarios, thyroid shielding reduced the equivalent dose for many tissues. The results indicate that the portion of the thyroid collar that wraps around the neck has the main role in reducing the effective dose during dental CBCT examinations, and the higher the axial level of the top of the shielding, the better the effectiveness of the shielding. In this study, the underestimation of the effective dose due to considering only the head and neck was 3.1%-8.1%, and the underestimation was more pronounced in larger FOVs.

Double-Layer Metasurface Integrated with Micro-LED for Naked-Eye 3D Display.

Naked-eye 3D micro-LED display combines the characteristics of 3D display with the advantages of micro-LED. However, the 3D micro-LED display is still at the conceptual stage, limited by its intrinsic emission properties of large divergence angle and non-coherence, as well as difficulties in achieving large viewing angles with high luminous efficiency. In this work, we propose a double-layer metasurface film integrating functions of collimation with multiple deflections, constituting a micro-LED naked-eye 3D display system. The system is characterized through numerical simulations using the 3D finite-difference time-domain method. The simulation results show that the double-layer metasurface film restricts 90% of the emitted light of the micro-LED to the vicinity of the 0° angle, improving its spatial coherence. Subsequently, a large-angle, low-crosstalk outgoing from -45° to 45° is achieved, while providing a deflection efficiency of over 80% and a pixel density of up to 605. We believe this design provides a feasible approach for realizing naked-eye 3D micro-LED displays with a large field of view, low crosstalk, and high resolution.

Large Field of View and Isotropic Light Sheet Microscopy with Aberration‐Free Tunable Foci

Large Field of View and Isotropic Light Sheet Microscopy with Aberration‐Free Tunable Foci

Lensless Mueller holographic microscopy with robust noise reduction for multiplane polarization imaging

Lensless holographic microscopy has emerged as a powerful and cost-effective tool for computational imaging, offering high resolution over a large field of view, beneficial for various biological applications. However, conventional approaches can struggle with contrast and accurate visualization of diverse components over the samples, which can directly affect the diagnostic precision of the techniques. Mueller imaging, while offering detailed, stain-free observations of polarized light responses in samples, often has a limited field of view and single plane information. This is due to the use of high NA microscope objectives and generally complex hardware setups, thus narrowing its practical effectiveness. This work introduces a Lensless Mueller Holographic Microscopy (LMHM) system that overcomes these limitations, enabling large field of view, volumetric multi-layer imaging, and Mueller matrix computation using in-line lens-free holography setup. The proposed system provides precision visualization of polarization information in samples, offering high-quality features due to the incorporation of a numerical multi-height Gerchberg-Saxton reconstruction algorithm with additional complex field filtering and a physical rotating diffuser. The proposed LMHM framework is validated with a calibrated USAF 1951 birefringent test target. A multiplane sample containing cloth fiber is utilized to study the LMHM capabilities of imaging volumetric samples. Finally, the LMHM is used to analyze two mice’s brain slices, effectively showcasing this organ’s anatomy. Among other structures in the brain, the proposed method easily allows the visualization of, e.g., the corpus callosum. These results constitute a proof-of-concept evaluation for bioimaging applications.