Single-shot Imaging Research Articles

Incoherent digital holography with two polarization-sensitive phase-only spatial light modulators and reduced number of exposures.

I propose methods for reducing the number of exposures in incoherent digital holography with two polarization-sensitive phase-only spatial light modulators (IDH with TPP-SLMs). In IDH with TPP-SLMs, no polarization filters are required, and not only three-dimensional (3D), but polarization information is also obtained. However, seven exposures are required to conduct filter-free polarimetric incoherent holography. In this article, the optical designs and modified phase-shifting interferometry to reduce the number of recordings are described. IDH with TPP-SLMs has the potential for filter-free single-shot multidimensional incoherent holographic imaging.

PortableSingle-Exposure Dual-Energy X-ray Detector for Improved Point-of-Care Diagnostic Imaging.

Dual-energy subtraction (DES) imaging is well known to reduce anatomical noise and enable material classification. The current approaches to DES imaging have trade-offs, such as motion artifacts, low sensitivity because of losses in a mid-filter, and lack of portability. Recently, a portable triple-layer flat-panel detector (FPD) was proposed for use in single-shot DES imaging that can provide improved sensitivity and removal of motion artifacts in a point-of-care setting. The purpose of this study is to evaluate the feasibility of such a detector. Various image quality metrics and clinical images are provided. An FDA-cleared single-exposure DES FPD consisting of three stacked sensors was used for all measurements. This detector generates three images per exposure: A digital radiography (DR) image, i.e., as would be produced with a conventional detector, and two DES images, bone and soft tissue. To evaluate DR image quality, detective quantum efficiency (DQE) and modulation transfer function were measured for multiple radiation quality beams. Digital radiography and DES images obtained from this FPD were evaluated in previously reported fixed and portable clinical studies. Digital radiography and DES images from case studies are presented for qualitative assessment. Modulation transfer function and DQE were measured across multiple radiation quality beams for the DR image. The DES images showed good tissue separation and uniformity with no visible motion or alignment artifacts. The DES images, when read in conjunction with the DR image, resulted in increased reader confidence and revealed abnormalities or details that were sometimes overlooked in the DR image. The proposed panel produces high-quality DR images as indicated by the DQE and modulation transfer function. The DES images have been shown to improve sensitivity in clinical applications and increase reader confidence. This detector can enable DES in portable or otherwise difficult applications, opening new doors for improved patient care.

Hyperspectral imaging through scattering media via physics-informed learning

Overcoming light scattering in natural light conditions is a challenging but rewarding problem. For this problem, both physics-based and data-driven methods encounter bottlenecks to recover large amounts of hyperspectral data encoded in the scattered light spot. In this paper, we present a physics-informed learning method to solve the light scattering problem with the neural network and the incoherent light transmission matrix method. With the proposed method, we achieve single-shot hyperspectral imaging through scattering media exceeding the memory effect range. Hyperspectral images with a maximum resolution of 3.2-megapixel are recovered in 64 wavebands, which represents an order of magnitude improvement over the memory effect range. No additional imaging or dispersion elements are required in the system except for the scatter medium, thus ensuring a compact and inexpensive hyperspectral imaging system. Our recovery method outperforms other physics-based and data-driven methods in terms of recovery quality and time cost.

Compressed single-shot 3D photoacoustic imaging with a single-element transducer

Three-dimensional (3D) photoacoustic imaging (PAI) can provide rich information content and has gained increasingly more attention in various biomedical applications. However, current 3D PAI methods either involves pointwise scanning of the 3D volume using a single-element transducer, which can be time-consuming, or requires an array of transducers, which is known to be complex and expensive. By utilizing a 3D encoder and compressed sensing techniques, we develop a new imaging modality that is capable of single-shot 3D PAI using a single-element transducer. The proposed method is validated with phantom study, which demonstrates single-shot 3D imaging of different objects and 3D tracking of a moving object. After one-time calibration, while the system could perform single-shot 3D imaging for different objects, the calibration could remain effective over 7 days, which is highly beneficial for practical translation. Overall, the experimental results showcase the potential of this technique for both scientific research and clinical applications.

Super-resolution imaging through scattering media based on improved triple correlation recursion and deterministic iterative estimation.

Iterative phase retrieval algorithms are commonly used in computational techniques and optimization methods to obtain the reconstruction of objects hidden behind opaque scattering media. However, these methods are susceptible to converging to incorrect local minima, and the calculation results tend to be unstable. In this paper, a triple-correlation-based super-resolution imaging (TCSI) framework is proposed to achieve single-shot imaging of unknown objects hidden behind the scattering medium. The amplitude spectrum of the object is obtained by a speckle correlation (SC) method. Iterative relaxation recursion (IRR) sufficiently extracts object information from the triple correlation (TC) of the speckle patterns, serving as the prior initial guess for the iterative estimation algorithm (IE) to obtain a deterministic phase spectrum. Blur correction (BC) is then applied to the diffraction-limited image to achieve super-resolution imaging. Experimental results demonstrate that the flexible framework could effectively overcome the influence of speckle resolution and outperform traditional methods in terms of performance. Our approach provides a basis for non-invasively visualizing various samples behind scattering media.

Single-shot, phase-diversity phase retrieval for high-energy beam focal-spot diagnostics

A single-shot, phase-diversity phase-retrieval method is demonstrated for directly characterizing the on-target focal spot at kilojoule energy in the OMEGA 60-beam laser. A 2D holographic grating that introduces diversity focal spots is installed in an existing on-target focal-spot diagnostic to obtain a single-shot diversity focal-spot image. A nonlinear optimization phase-retrieval algorithm with four diversity focal spots is employed to determine modal coefficients for the incident wavefront. The agreement between the measured and calculated focal spots is excellent. This approach can be easily adapted for other high-energy focal-spot diagnostics.

Single-shot wide-field full-stokes polarization imaging

Polarization is an intrinsic property of light. With the advancements in nanophotonics, it is now possible to achieve arbitrary polarization transformations in space. Incorporating special functions in different spatial dimensions expands the design freedom of metasurfaces and other optical devices. To understand and utilize the metasurface, we design a metasurface optical element to achieve single-shot, wide-field polarization imaging. Our demonstration exhibits a compact, full Stokes wide-field polarization imaging device without requiring conventional optical elements, such as moving parts or wide-field lens sets. Wide-field polarization imaging devices are potential candidates for machine vision and biological tissue imaging applications.

Polarization differential interference contrast microscopy with physics-inspired plug-and-play denoiser for single-shot high-performance quantitative phase imaging.

We present single-shot high-performance quantitative phase imaging with a physics-inspired plug-and-play denoiser for polarization differential interference contrast (PDIC) microscopy. The quantitative phase is recovered by the alternating direction method of multipliers (ADMM), balancing total variance regularization and a pre-trained dense residual U-net (DRUNet) denoiser. The custom DRUNet uses the Tanh activation function to guarantee the symmetry requirement for phase retrieval. In addition, we introduce an adaptive strategy accelerating convergence and explicitly incorporating measurement noise. After validating this deep denoiser-enhanced PDIC microscopy on simulated data and phantom experiments, we demonstrated high-performance phase imaging of histological tissue sections. The phase retrieval by the denoiser-enhanced PDIC microscopy achieves significantly higher quality and accuracy than the solution based on Fourier transforms or the iterative solution with total variance regularization alone.

Transient susceptibility imaging as a measure of hemodynamic compromise: A pilot study

Background and purposeThe purpose of this study was to test the hypothesis that hemodynamically compromised brains exhibit transient changes in magnetic susceptibility throughout the cardiac cycle, and to model these changes using Linear System Theory to extract an index that reflects cerebrovascular reserve. Materials and methodsEleven patients with angiographically-confirmed intracranial atherosclerotic disease with >50% stenosis were imaged with susceptibility weighted, cardiac-gated single shot images of cerebral Oxygen Extraction Fraction (OEF) at different timepoints of the cardiac cycle. Cardiac gating of the OEF acquisition allowed interrogation of oxygenated blood and the detection of changes throughout the cardiac cycle. Independent component analysis (ICA) of raw k-space data across the cardiac phase allowed MRI signal decomposition into dynamic and static components for image reconstruction. An asymmetry index score of the resultant parametric images were compared to test the hypothesis that variation in hemoglobin-induced susceptibility across the cardiac cycle indeed reflects pathophysiology of cerebrovascular disease. A mathematical model was derived to parameterize physiologic changes induced by the presence of a hemodynamically significant stenosis in the brain as a tissue impulse response parameter (β). ResultsOEF was elevated in the affected hemisphere (50.34 ± 12.13% vs 46.93 ± 12.34%), but failed to reach statistical significance (p < .0796). Transient changes in the OEF signal showed significant distinction between healthy and compromised tissue (0.56 ± 0.067 vs 0.44 ± 0.067, p < .019)). The derived tissue impulse response function was found to be significant as well (10.72 ± 3.48 10−3 ms−1, 9.69 ± 3.51 10−3 ms−1; p < .037). ConclusionIn this pilot study, we found transient OEF and β to be significant predictors of hemispheric compromise.

Single-shot quantitative x-ray imaging using a primary modulator and dual-layer detector.

Conventional x-ray imaging and fluoroscopy have limitations in quantitation due to several challenges, including scatter, beam hardening, and overlapping tissues. Dual-energy (DE) imaging, with its capability to quantify area density of specific materials, is well-suited to address such limitations, but only if the dual-energy projections are acquired with perfect spatial and temporal alignment and corrected for scatter. In this work, we propose single-shot quantitative imaging (SSQI) by combining the use of a primary modulator (PM) and dual-layer (DL) detector, which enables motion-free DE imaging with scatter correction in a single exposure. The key components of our SSQI setup include a PM and DL detector, where the former enables scatter correction for the latter while the latter enables beam hardening correction for the former. The SSQI algorithm allows simultaneous recovery of two material-specific images and two scatter images using four sub-measurements from the PM encoding. The concept was first demonstrated using simulation of chest x-ray imaging for a COVID patient. For validation, we set up SSQI geometry on our tabletop system and imaged acrylic and copper slabs with known thicknesses (acrylic: 0-22.5cm; copper: 0-0.9mm), estimated scatter with our SSQI algorithm, and compared the material decomposition (MD) for different combinations of the two materials with ground truth. Second, we imaged an anthropomorphic chest phantom containing contrast in the coronary arteries and compared the MD with and without SSQI. Lastly, to evaluate SSQI in dynamic applications, we constructed a flow phantom that enabled dynamic imaging of iodine contrast. Our simulation study demonstrated that SSQI led to accurate scatter correction and MD, particularly for smaller focal blur and finer PM pitch. In the validation study, we found that the root mean squared error (RMSE) of SSQI estimation was 0.13cm for acrylic and 0.04mm for copper. For the anthropomorphic phantom, direct MD resulted in incorrect interpretation of contrast and soft tissue, while SSQI successfully distinguished them quantitatively, reducing RMSE in material-specific images by 38%-92%. For the flow phantom, SSQI was able to perform accurate dynamic quantitative imaging, separating contrast from the background. We demonstrated the potential of SSQI for robust quantitative x-ray imaging. The integration of SSQI is straightforward with the addition of a PM and upgrade to a DL detector, which may enable its widespread adoption, including in techniques such as radiography and dynamic imaging (i.e., real-time image guidance and cone-beam CT).

Feasibility of cardiac MR thermometry at 0.55 T.

Radiofrequency catheter ablation is an established treatment strategy for ventricular tachycardia, but remains associated with a low success rate. MR guidance of ventricular tachycardia shows promises to improve the success rate of these procedures, especially due to its potential to provide real-time information on lesion formation using cardiac MR thermometry. Modern low field MRI scanners (<1 T) are of major interest for MR-guided ablations as the potential benefits include lower costs, increased patient access and device compatibility through reduced device-induced imaging artefacts and safety constraints. However, the feasibility of cardiac MR thermometry at low field remains unknown. In this study, we demonstrate the feasibility of cardiac MR thermometry at 0.55 T and characterized its in vivo stability (i.e., precision) using state-of-the-art techniques based on the proton resonance frequency shift method. Nine healthy volunteers were scanned using a cardiac MR thermometry protocol based on single-shot EPI imaging (3 slices in the left ventricle, 150 dynamics, TE = 41 ms). The reconstruction pipeline included image registration to align all the images, multi-baseline approach (look-up-table length = 30) to correct for respiration-induced phase variations, and temporal filtering to reduce noise in temperature maps. The stability of thermometry was defined as the pixel-wise standard deviation of temperature changes over time. Cardiac MR thermometry was successfully acquired in all subjects and the stability averaged across all subjects was 1.8 ± 1.0°C. Without multi-baseline correction, the overall stability was 2.8 ± 1.6°C. In conclusion, cardiac MR thermometry is feasible at 0.55 T and further studies on MR-guided catheter ablations at low field are warranted.

Design and characterization of a varifocal camera system with an extended depth of field and focal range.

This paper presents the design and characterization of a compact and affordable varifocal camera system. With its entrance pupil located in front as the first element for easy access, the camera system offers a working F/# as low as 2, is capable of focusing across a wide depth range from optical infinity to as close as 4 diopters through an electrically tunable lens, and maintains nearly constant angular magnification through the focus range by placing the focusing element at proximity to the entrance pupil. These unique features can find a myriad of applications such as image-based head-mounted display calibration and extended depth of field (EDOF) imaging. The paper further demonstrates a single-shot EDOF imaging function by utilizing its property of nearly constant angular magnification through focus scanning.

Measurements of mixing layers and vortex structures of the strut-induced flow in a scramjet combustor with PIV and POD

The organization of the flow field in a scramjet is of great significance in achieving stable combustion in supersonic flow. Experimental investigation of the strut-induced flow in a scramjet is conducted with particle image velocimetry (PIV) measurement. The central wakes along with two outer free streams can be observed in the instantaneous velocity fields. Then the calculated vorticity shows a similar distribution with the mixing layers in the single-shot image, suggesting the mixing layers a preliminary assessment of the flow. Proper orthogonal decomposition (POD) of snapshots reveals several features beneficial for flame stabilization in the strut-induced flow, including the reverse flow, central large-scale vortex structures and the vortex structures in the mixing layers. Moreover, by comparison it is found that a significant asymmetry of strut-induced flow would compress the low-speed region and weaken the large-scale vortex structure which would present a challenge to achieve flame establishment. The research contributes to a profound understanding of strut-induced flow which may be useful for engineering design and optimization.

Resolution enhancement via guided filtering for spatial-frequency multiplexing single-shot high-speed imaging.

The frequency recognition algorithm for multiple exposures (FRAME) is a progressive single-shot high-speed videography technique that employs the spatial-frequency multiplexing concept to provide high temporal and spatial resolution. However, the inherent crosstalk from the zero-frequency component to the carrier-frequency component leads to resolution degradation and artifacts. To improve recovered frames' quality, we propose a FRAME reconstruction method using guided filters for a removal of the zero-frequency component, which can minimize the artifacts while enhance spatial resolution. A total variation (TV) denoising operation is involved to remove artifacts further to achieve optimized performances. Simulations and experiments were conducted to demonstrate the robust and efficient post-processing capability of the proposed method. With a two-frame experimental system, the results of a USAF 1951 resolution target reveal a 1.8-fold improvement in spatial resolution from 16 lp/mm to 28.5 lp/mm. For complex dynamic scenarios, the wide field of high-speed fuel spray was shot and the proposed method can resolve two droplets with a 30 μm distance which outperforms the traditional method.

Single-Shot Quantitative Polarization Imaging of Live Cancer Cells

Single-Shot Quantitative Polarization Imaging of Live Cancer Cells

Dual-view transport of intensity phase imaging flow cytometry.

In this work, we design multi-parameter phase imaging flow cytometry based on dual-view transport of intensity (MPFC), which integrates phase imaging and microfluidics to a microscope, to obtain single-shot quantitative phase imaging on cells flowing in the microfluidic channel. The MPFC system has been proven with simple configuration, accurate phase retrieval, high imaging contrast, and real-time imaging and has been successfully employed not only in imaging, recognizing, and analyzing the flowing cells even with high-flowing velocities but also in tracking cell motilities, including rotation and binary rotation. Current results suggest that our proposed MPFC provides an effective tool for imaging and analyzing cells in microfluidics and can be potentially used in both fundamental and clinical studies.

Single-shot image restoration via a model-enhanced network with unpaired supervision in an optical sparse aperture system.

We propose a model-enhanced network with unpaired single-shot data for solving the imaging blur problem of an optical sparse aperture (OSA) system. With only one degraded image captured from the system and one "arbitrarily" selected unpaired clear image, the cascaded neural network is iteratively trained for denoising and restoration. With the computational image degradation model enhancement, our method is able to improve contrast, restore blur, and suppress noise of degraded images in simulation and experiment. It can achieve better restoration performance with fewer priors than other algorithms. The easy selectivity of unpaired clear images and the non-strict requirement of a custom kernel make it suitable and applicable for single-shot image restoration of any OSA system.

Chip-integrated metasurface full-Stokes polarimetric imaging sensor

Polarimetric imaging has a wide range of applications for uncovering features invisible to human eyes and conventional imaging sensors. Chip-integrated, fast, cost-effective, and accurate full-Stokes polarimetric imaging sensors are highly desirable in many applications, which, however, remain elusive due to fundamental material limitations. Here we present a chip-integrated Metasurface-based Full-Stokes Polarimetric Imaging sensor (MetaPolarIm) realized by integrating an ultrathin (~600 nm) metasurface polarization filter array (MPFA) onto a visible imaging sensor with CMOS compatible fabrication processes. The MPFA is featured with broadband dielectric-metal hybrid chiral metasurfaces and double-layer nanograting polarizers. This chip-integrated polarimetric imaging sensor enables single-shot full-Stokes imaging (speed limited by the CMOS imager) with the most compact form factor, records high measurement accuracy, dual-color operation (green and red) and a field of view up to 40 degrees. MetaPolarIm holds great promise to enable transformative applications in autonomous vision, industry inspection, space exploration, medical imaging and diagnosis.

Single-shot ultrafast dual-view imaging of shock waves in parallel laser processing

Single-shot ultrafast optical imaging has revealed various non-repetitive processes, but it has conventionally provided only single-view measurements. Here, we demonstrate a single-shot ultrafast dual-view imaging technique by monitoring shock waves in laser processing of glass using single or parallelized excitation pulses. We visualize the spatiotemporal evolution of shock waves in air at 0.5 Gfps with five frames in both top and side views, indicating the velocity anisotropy and interaction of shock waves. Our technique can contribute to a comprehensive understanding not only of shock wave dynamics but also of other spatially complex ultrafast phenomena including laser-induced plasma and electrical discharge.

Automatic Localization of the Pons and Vermis on Fetal Brain MR Imaging Using a U-Net Deep Learning Model.

An MRI of the fetus can enhance the identification of perinatal developmental disorders, which improves the accuracy of ultrasound. Manual MRI measurements require training, time, and intra-variability concerns. Pediatric neuroradiologists are also in short supply. Our purpose was developing a deep learning model and pipeline for automatically identifying anatomic landmarks on the pons and vermis in fetal brain MR imaging and suggesting suitable images for measuring the pons and vermis. We retrospectively used 55 pregnant patients who underwent fetal brain MR imaging with a HASTE protocol. Pediatric neuroradiologists selected them for landmark annotation on sagittal single-shot T2-weighted images, and the clinically reliable method was used as the criterion standard for the measurement of the pons and vermis. A U-Net-based deep learning model was developed to automatically identify fetal brain anatomic landmarks, including the 2 anterior-posterior landmarks of the pons and 2 anterior-posterior and 2 superior-inferior landmarks of the vermis. Four-fold cross-validation was performed to test the accuracy of the model using randomly divided and sorted gestational age-divided data sets. A confidence score of model prediction was generated for each testing case. Overall, 85% of the testing results showed a ≥90% confidence, with a mean error of <2.22 mm, providing overall better estimation results with fewer errors and higher confidence scores. The anterior and posterior pons and anterior vermis showed better estimation (which means fewer errors in landmark localization) and accuracy and a higher confidence level than other landmarks. We also developed a graphic user interface for clinical use. This deep learning-facilitated pipeline practically shortens the time spent on selecting good-quality fetal brain images and performing anatomic measurements for radiologists.