Coherence Tomography Research Articles

Diffractive Optical Encryption Systems Based on Multiple Wavelengths and Multiple Distances

Coherent diffractive imaging is an optical methodology that encodes information about an object within the diffraction intensity. Here, we introduce a diffractive optical encryption system that utilizes multiple wavelengths and multiple distances, significantly expanding the size of the secret key space and enhancing the overall security of the system by incorporating these parameters as keys. The system adopts single optical path design, compact structure and is easy to implement, overcoming the disadvantage of single key space of traditional encryption system. This system can encrypt images into a series of diffraction intensity maps (i.e., ciphertexts), and exhibits a high sensitivity to minor variations in wavelength or distance during the process of decryption, showing excellent anti-cracking ability. Furthermore, the system also has considerable robustness, ensuring that the information still can be effectively recovered even in instances of partial loss. Numerical simulation results are presented to demonstrate feasibility and effectiveness of the proposed method. Our study provides novel concepts and methodologies to the advancement of optical encryption technology, while also offering significant technical assistance to the domain of information security.

Automated defect identification in coherent diffraction imaging with smart continual learning

Automated defect identification in coherent diffraction imaging with smart continual learning

SAR-NTV-YOLOv8: A Neural Network Aircraft Detection Method in SAR Images Based on Despeckling Preprocessing

Monitoring aircraft using synthetic aperture radar (SAR) images is a very important task. Given its coherent imaging characteristics, there is a large amount of speckle interference in the image. This phenomenon leads to the scattering information of aircraft targets being masked in SAR images, which is easily confused with background scattering points. Therefore, automatic detection of aircraft targets in SAR images remains a challenging task. For this task, this paper proposes a framework for speckle reduction preprocessing of SAR images, followed by the use of an improved deep learning method to detect aircraft in SAR images. Firstly, to improve the problem of introducing artifacts or excessive smoothing in speckle reduction using total variation (TV) methods, this paper proposes a new nonconvex total variation (NTV) method. This method aims to ensure the effectiveness of speckle reduction while preserving the original scattering information as much as possible. Next, we present a framework for aircraft detection based on You Only Look Once v8 (YOLOv8) for SAR images. Therefore, the complete framework is called SAR-NTV-YOLOv8. Meanwhile, a high-resolution small target feature head is proposed to mitigate the impact of scale changes and loss of depth feature details on detection accuracy. Then, an efficient multi-scale attention module was proposed, aimed at effectively establishing short-term and long-term dependencies between feature grouping and multi-scale structures. In addition, the progressive feature pyramid network was chosen to avoid information loss or degradation in multi-level transmission during the bottom-up feature extraction process in Backbone. Sufficient comparative experiments, speckle reduction experiments, and ablation experiments are conducted on the SAR-Aircraft-1.0 and SADD datasets. The results have demonstrated the effectiveness of SAR-NTV-YOLOv8, which has the most advanced performance compared to other mainstream algorithms.

Imaging of micro-steps on as-grown surface of sapphire with X-ray phase contrast technique

Basal-faceted sapphire ribbons grown using the Stepanov–LaBelle technology have a low density of surface steps. We present our results on a study of steps on the surface of a ribbon, misoriented relative to the singular face (0001) by several arc minutes. The ribbon has been characterized by means of in-line phase contrast imaging technique at Pohang Light Source, South Korea. It was shown for the first time that a step height of about 1 μm can be determined directly from an image. The step height obtained using the phase contrast method was confirmed by atomic force microscopy measurements. We have found that the experimental contrast matches the theoretical simulations only if the calculated intensity profile has been convolved with a Gaussian function. The full width at half maximum of the Gaussian was independently got from previous measurements. We have obtained an analytical solution in the case of theoretical fully coherent phase contrast image. The inverse problem is easy to solve, since there is a direct proportionality between the contrast and the step height.

A tunable spatial coherence imaging with ultrasonic array for defects in composites

ABSTRACT Ultrasonic phased array detection technology is a promising non-destructive testing (NDT) method that has been widely used for defect detection. Due to the high attenuation characteristics of ultrasonic wave propagation in carbon fibre reinforced polymer (CFRP) and the directivity of the array elements, the possibility of false or missed detection for defects that are far from the array elements or located very close together will increase. In addition, the total focusing method (TFM) employs only the defect information contained in the full matrix capture (FMC) dataset while ignoring the spatial information of the array signals, leading to image mixed with artefact and noise. An improved method called p-weighted-TFM (p-WTFM) is proposed. First, this method scales the magnitude of time-delayed channel signal by p-th root while maintaining the phase unchanged. Second, channel summation with energy compensation and directional correction will be realised. Finally, the signal dimensionality is restored by p-th power. Experimental results show that the p-WTFM can use any rational p-value to flexibly adjust image quality. Specially, this method can accurately distinguish adjacent defects spaced 1 mm apart with p value of 2.5, and it can also detect two defects located 10 mm deep with p value of 3.0.

Label-free functional imaging of vagus nerve stimulation-evoked potentials at the cortical surface

Vagus nerve stimulation (VNS) is an FDA-approved stimulation therapy to treat patients with refractory epilepsy. In this work, we use a coherent holographic imaging system to characterize vagus nerve-evoked potentials (VEPs) in the cortex in response to VNS stimulation paradigms without electrode placement or any genetic, structural, or functional labels. We analyze stimulation amplitude up to saturation, pulse width up to 800 μs, and frequency from 10 Hz to 30 Hz, finding that stimulation amplitude strongly modulates VEPs response magnitude (effect size 0.401), while pulse width has a moderate modulatory effect (effect size 0.127) and frequency has almost no modulatory effect (effect size 0.009) on the evoked potential magnitude. We find mild interactions between pulse width and frequency. This non-contact label-free functional imaging technique may serve as a non-invasive rapid-feedback tool to characterize VEPs and may increase the efficacy of VNS in patients with refractory epilepsy.

Speckle denoising based on Swin-UNet in digital holographic interferometry

Speckle noise, mechano-physical noise, and environmental noise are inevitably introduced in digital holographic coherent imaging, which seriously affects the quality of phase maps, and the removal of non-Gaussian statistical noise represented by speckle noise has been a challenging problem. In the past few years, deep learning methods based on convolutional neural networks (CNNs) have made good progress in removing Gaussian noise. However, they tend to fail when these deep networks designed for Gaussian noise removal are used to remove speckle noise. Recently, numerous studies have employed CNNs to address the issue of degraded speckle images, yielding encouraging results. Nevertheless, the degradation of speckle noise that is simulated in isolation is limited and insufficient to encompass the increasingly complex DHI noise environment. This paper presents what we believe to be a novel approach to simulating complex noise environments by multiplexing simulated Gaussian noise and speckle noise. The noise resulting from aliasing does not adhere to the statistical laws of the noise prior to aliasing, which poses a more challenging task for the noise-reduction algorithms utilized in neural networks. Consequently, in conjunction with the capacity of the Swin Transformer to model multi-scale features, this paper proposes a DHI speckle denoising approach based on Swin-UNet. In this paper, Gaussian, speckle, and blending noise datasets with different noise densities are constructed for training and testing by numerical simulation, and generalizability tests are performed on 1,100 randomly selected open-source holographic tomography (HT) noise images at Warsaw University of Technology and 25 speckle images selected from DATABASE. All test results are quantitatively evaluated by three evaluation metrics: mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM). All convolutional neural network (CNN) algorithms are evaluated qualitatively based on the number of parameters, floating point operations, and denoising time. The results of the comparison demonstrate that the denoising algorithm presented in this paper exhibits greater stability, accuracy, and generalizability.

Bragg coherent diffractive imaging for defects analysis: Principles, applications, and challenges

Bragg coherent diffractive imaging for defects analysis: Principles, applications, and challenges

Snapshot coherent diffraction imaging across ultra-broadband spectra

Ultrafast imaging simultaneously pursuing high temporal and spatial resolution is a key technique to study the dynamics in the microscopic world. However, the broadband spectra of ultra-short pulses bring a major challenge to traditional coherent diffraction imaging (CDI), as they result in an indistinct diffraction pattern, thereby complicating image reconstruction. To address this, we introduce, to our knowledge, a new ultra-broadband coherent imaging method, and empirically demonstrate its efficacy in facilitating high-resolution and rapid image reconstruction of achromatic objects. The existing full bandwidth limitation for snapshot CDI is enhanced to ∼60% experimentally, restricted solely by our laser bandwidth. Simulations indicate the applicability of our method for CDI operations with a bandwidth as high as ∼140%, potentially supporting ultrafast imaging with temporal resolution into ∼50-attosecond scale. Even deployed with a comb-like harmonic spectrum encompassing multiple octaves, our method remains effective. Furthermore, we establish the capability of our approach in reconstructing a super-broadband spectrum for CDI applications with high fidelity. Given these advancements, we anticipate that our method will contribute significantly to attosecond imaging, thereby advancing cutting-edge applications in material science, quantum physics, and biological research.

Coherent X-ray diffraction imaging of single particles: background impact on 3D reconstruction.

Coherent diffractive imaging with X-ray free-electron lasers could enable structural studies of macromolecules at room temperature. This type of experiment could provide a means to study structural dynamics on the femtosecond timescale. However, the diffraction from a single protein is weak compared with the incoherent scattering from background sources, which negatively affects the reconstruction analysis. This work evaluates the effects of the presence of background on the analysis pipeline. Background measurements from the European X-ray Free-Electron Laser were combined with simulated diffraction patterns and treated by a standard reconstruction procedure, including orientation recovery with the expand, maximize and compress algorithm and 3D phase retrieval. Background scattering did have an adverse effect on the estimated resolution of the reconstructed density maps. Still, the reconstructions generally worked when the signal-to-background ratio was 0.6 or better, in the momentum transfer shell of the highest reconstructed resolution. The results also suggest that the signal-to-background requirement increases at higher resolution. This study gives an indication of what is possible at current setups at X-ray free-electron lasers with regards to expected background strength and establishes a target for experimental optimization of the background.

Image inpainting algorithm based on inference attention module and two-stage network

Current image inpainting techniques often yield distorted structures or blurred textures that clash with the surrounding context, particularly when addressing extensive missing regions or highly textured images. These methods often struggle to reconstruct realistic and coherent image structures. To address this challenge, we introduce a two-stage network image restoration approach that leverages an inferential attention mechanism. In the first stage, an edge generation network is employed to produce plausible phantom edge information. Subsequently, an image complementation network is utilized to complete the image restoration process. To enhance the visual realism and restoration accuracy of the generated images, we incorporate an inferential attention mechanism within the image complementation network. This mechanism effectively mitigates inconsistencies in the generated features, leading to the production of more meaningful and effective information. We evaluate our proposed method on benchmark datasets, including Places2 dataset, CelebFaces Attributes dataset, and Paris StreetView dataset. The experimental results can demonstrate that the proposed method achieves better Structural Similarity Index and Peak Signal-to-noise Ratio than others. These metrics indicate superior performance compared to existing image inpainting methods, delivering higher image inpainting accuracy and more realistic image reconstruction effect.

Ultra-broadband diffractive imaging with unknown probe spectrum

Strict requirement of a coherent spectrum in coherent diffractive imaging (CDI) architectures poses a significant obstacle to achieving efficient photon utilization across the full spectrum. To date, nearly all broadband computational imaging experiments have relied on accurate spectroscopic measurements, as broad spectra are incompatible with conventional CDI systems. This paper presents an advanced approach to broaden the scope of CDI to ultra-broadband illumination with unknown probe spectrum, effectively addresses the key challenges encountered by existing state-of-the-art broadband diffractive imaging frameworks. This advancement eliminates the necessity for prior knowledge of probe spectrum and relaxes constraints on non-dispersive samples, resulting in a significant extension in spectral bandwidth, achieving a nearly fourfold improvement in bandlimit compared to the existing benchmark. Our method not only monochromatizes a broadband diffraction pattern from unknown illumination spectrum, but also determines the compressive sampled profile of spectrum of the diffracted radiation. This superiority is experimentally validated using both CDI and ptychography techniques on an ultra-broadband supercontinuum with relative bandwidth exceeding 40%, revealing a significantly enhanced coherence and improved reconstruction with high fidelity under ultra-broadband illumination.

Impact of corner radius of the aperture on the accuracy of phase retrieval analysis in single-frame CDI for nanomaterials

Numerous efforts have been developed to advance the process of Ptychography, leading to the emergence of a phenomenon known as single-frame Coherent X-ray Diffraction Imaging (CDI). It represents an advanced form of Ptychography in which a well-defined coherent X-ray beam is directed onto the sample to generate a diffraction image that includes intensity information but lacks phase details. However, phase retrieval in single-frame CDI faces challenges like overlapping loss, inadequate samples, or phase ambiguity due to the characteristics of this method. The optimising effort has been conducted in the form of aperture implementation to address these problems, particularly in the iterative phase retrieval domain. This study explores non-point symmetrical apertures, specifically triangles, to enhance image reconstruction quality in iterative phase retrieval. We developed a simulation methodology to explore the impact of corner radius on the apertures in performing single-frame CDI. Our simulator generates diffraction images for each shape, which are processed through iterative algorithms and deep learning to reconstruct images. The effectiveness of each shape is assessed by visualising the loss function results, providing insights into optimal aperture designs for diffraction imaging, and contributing to the resolution of phase retrieval challenges in single-frame CDI.

Optical coherence tomography quantifies gradient refractive index and mechanical stiffness gradient across the human lens

BackgroundAs a key element of ocular accommodation, the inherent mechanical stiffness gradient and the gradient refractive index (GRIN) of the crystalline lens determine its deformability and optical functionality. Quantifying the GRIN profile and deformation characteristics in the lens has the potential to improve the diagnosis and follow-up of lenticular disorders and guide refractive interventions in the future.MethodsHere, we present a type of optical coherence elastography able to examine the mechanical characteristics of the human crystalline lens and the GRIN distribution in vivo. The concept is demonstrated in a case series of 12 persons through lens displacement and strain measurements in an age-mixed group of human subjects in response to an external (ambient pressure modulation) and an intrinsic (micro-fluctuations of accommodation) mechanical deformation stimulus.ResultsHere we show an excellent agreement between the high-resolution strain map retrieved during steady-state micro-fluctuations and earlier reports on lens stiffness in the cortex and nucleus suggesting a 2.0 to 2.3 times stiffer cortex than the nucleus in young lenses and a 1.0 to 7.0 times stiffer nucleus than the cortex in the old lenses.ConclusionsOptical coherence tomography is suitable to quantify the internal stiffness and refractive index distribution of the crystalline lens in vivo and thus might contribute to reveal its inner working mechanism. Our methodology provides new routes for ophthalmic pre-surgical examinations and basic research.

Coherent ghost imaging via phase compensation

The 4-f optical illumination structure is widely used in coherent ghost imaging (CGI) system but its imaging field of view (FOV) is usually restricted by the transmission aperture of the lens. Therefore, this optical illumination structure cannot be applied to remote imaging. Based on conventional imaging illumination structure, a large-FOV CGI via phase compensation (CGI-PC) is proposed and its imaging property is investigated. The experimental results demonstrate that both the FOV and the quality of CGI can be dramatically improved when a lens is introduced into the receiving system to compensate the system’s spatial phase difference. Factors influencing the quality of CGI-PC are also discussed.

(Battery Student Slam 8 Award Winner) Multi-Clustered Lithium Diffusion in Single-Crystalline NMC Battery Particles

Understanding the diffusion dynamics of lithium within solid-state electrodes is pivotal for developing high-performance batteries. In this context, layered oxides were utilized as a promising cathode material due to their high energy density and fast intraparticle lithium diffusivity. Despite advancements in material composition, coating, and doping, the understanding of intraparticle lithium diffusion has long been described by Fick's law. Conventionally, lithium diffusion is assumed to generate a monotonic lithium concentration gradient within solid-solution single-crystalline battery materials during cycling. This raises fundamental questions about diffusion in layered oxides; (1) Can the diffusion of Li in solids be interpreted as Fickian diffusion, similar to diffusion in gases or liquids, even though it involves structural and phase evolution throughout the battery cycle? and, (2) Does the fast diffusivity (10-11-10-9 cm2/s) support the homogenization of Li?In this study, we address these questions surrounding lithium diffusion in layered oxide by utilizing operando scanning transmission X-ray microscopy. We revealed the formation of mobile Li-dense/-dilute nano-domains within individual single-crystalline LiNi1/3Mn1/3Co1/3O2 (scNMC) during battery cycles. We term this phenomenon ‘multi-clustered lithium diffusion’, distinguishing our findings from the conventionally suggested Fickian diffusion model in solid-solution materials. These domains persist for at least 4 hours during relaxation, accompanied by locally residing strained domains, as confirmed by Bragg coherent diffraction imaging (BCDI), within a single particle. We believe these domains arise due to the compensation of localized chemical potential gradients that are generated by the sustained presence of strain within the battery particles during cycling.While maintaining integrity of Li-dense/-dilute domain at various C-rates, STXM result further show that Li-dilute domains maintain during the discharging. Given the lower concentration of Li at insertion boundaries, which could lower the surface charge transfer impedance of the system, Li-dilute domains facilitate lithium transport by functioning as low-resistance pathways. Through a comprehensive analysis of electrical impedance spectroscopy (EIS), STXM imaging and finite element analysis (FEA), we showed that controlling the local domain fraction is crucial for controlling the overpotential during subsequent charging. Our study introduces new insights into nanoscale solid-state diffusion, thereby enabling the fabrication of high-performance batteries. Figure 1

(Invited) Bragg Coherent Diffraction Imaging Studies of Composition Distribution and Strain in Catalytic Alloy Nanoparticles

Compositional distribution, strain, and defects in alloy nanoparticles significantly affect the catalytic properties for a wide range of applications such as gas reforming, fuel cells, electrolysis, etc. while various alloy compositions of nanoparticles have been investigated to improve performance and reduce the amount of precious metals used. It was reported that the composition distribution of the alloy particles, expectedly homogeneous in the whole particle, changed dynamically depending on the operating environment, resulting in altering the catalytic activity [1]. Furthermore, defects such as dislocations, grain boundaries, and elastic strain of the crystalline lattice also significantly affect catalytic properties. Since these factors dynamically change and evolve under operating environments, in situ measurements are essential to reveal these factors and ultimately to exploit them to enhance the catalytic properties. Bragg coherent diffraction imaging (BCDI) is a lens-less imaging method that measures speckle patterns near Bragg diffraction from a crystalline sample and reconstructs the 3D particle images. Since Bragg diffraction is inherently sensitive to displacements of the crystal lattice, BCDI yields the displacement field within the sample as well as the electron density, i.e., the “shape” of the particle. This displacement field information further allows us to evaluate strain distribution, dislocations, and composition distribution in the particle. BCDI is also advantageous for in situ measurements because the 3D image can be obtained by rotating the sample by only a few degrees, which eases the geometrical constraint of an electrochemical cell for the measurement. This is in contrast to conventional 3D imaging techniques such as X-ray CT, which usually requires 180 degrees of sample rotation.Furthermore, it is expected that the measurement capabilities of BCDI will be rapidly advanced by upgrading synchrotron radiation facilities such as APS-U, which delivers high-flux coherent X-rays. This should expand the applications of BCDI to wider electrochemical materials. In this presentation, we will briefly overview the principle of BCDI followed by specific examples of in situ measurements of catalytic alloy particles [2-4] conducted at 34-ID-C at Advanced Photon Source.[1] F. Tao et al., Science 322, 932 (2008).[2] T. Kawaguchi et al., Phys. Rev. Lett. 123, 246001 (2019).[3] T. Kawaguchi et al., Nano Lett. 21, 5945 (2021).[4] D. Sheyfer, R. G. Mariano, T. Kawaguchi, et al., Nano Lett. 23, 1 (2023).

Dynamic Coupling of Internal Strain Field and Lithium Pathway within Individual Battery Particles in Solid State Batteries

In all-solid-state batteries (ASSBs), (electro)chemo-mechanical aspects such as uneven interfaces, cathode-electrolyte interphase formation, delamination, fracture, defects, etc., are the major factors in capacity fade but remain largely unknown.Nonhomogeneous transfer of lithium ions can cause significant variations in strain and stress within battery electrodes, leading to degradation in battery performance. In all-solid-state batteries (ASSBs), the lithium pathway and the associated strain/stress field become more intricate due to the (electro)chemo-mechanical reaction at the electrode-electrolyte interfaces. The dynamic volume change in active particles are heavily influencing by strength of the solid electrolyte and interfacial conformality. This can continually alter the lithium pathway and the internal stress field, leading to recurrent redefinitions of (electro)chemo-mechanical environment.Here, we have developed an operando coherent X-ray imaging platform and associated analysis methodologies. This technology can track the nanoscale transport of lithium and the strain evolution of individual electrode particles in ASSBs. With this platform, we gained a comprehensive electrochemical and mechanical understanding of the cycling properties of single electrode particles in ASSBs.

Correcting angular distortions in Bragg coherent X-ray diffraction imaging.

Bragg coherent X-ray diffraction imaging (BCDI) has emerged as a powerful technique for strain imaging and morphology reconstruction of nanometre-scale crystals. However, BCDI often suffers from angular distortions that appear during data acquisition, caused by radiation pressure, heating or imperfect scanning stages. This limits the applicability of BCDI, in particular for small crystals and high-flux X-ray beams. Here, we present a pre-processing algorithm that recovers the 3D datasets from the BCDI dataset measured under the impact of large angular distortions. We systematically investigate the performance of this method for different levels of distortion and find that the algorithm recovers the correct angles for distortions up to 16.4× (1640%) the angular step size dθ = 0.004°. We also show that the angles in a continuous scan can be recovered with high accuracy. As expected, the correction provides marked improvements in the subsequent phase retrieval.

The Macular Pigment Optical Density (MPOD) Decrease in Chinese Primary Angle Closure Glaucoma Using the One-Wavelength Reflectometry Method

Purpose The objective of this study was to observe the macular pigment optical density (MPOD) and the relationship between MPOD and retinal thickness in Chinese primary angle-closure glaucoma (PACG) patients by the one-wavelength reflectometry method. Methods This study was a prospective comparative observational study, including 39 eyes from 39 PACG patients (15 men and 24 women, mean age 61.89 ± 12.30) and 41 eyes from 41 controls (20 men and 21 women, mean age 63.24 ± 14.02). We measured the MPOD 7-degree area by the one-wavelength reflectometry method and analyzed both the max and mean optical density (OD). The central retinal thickness (CRT) and the total thickness of the macular ganglion cell layer (GCL), and inner plexiform layer (IPL)were measured by spectral-domain-optical coherence tomography (SD-OCT). Statistical methods such as Shapiro–Wilk test, Fisher’s exact test, chi-square test, two independent samples test and Spearman’s correlation coefficient were used to observe the differences in the MPOD between normal subjects and PACG patients and the correlation between the MPOD and retinal thickness. Results The max optical density (Max OD) (PACG group: 0.302 ± 0.067d.u, control group: 0.372 ± 0.059d.u., p < .001) and mean optical density (Mean OD) (PACG group: 0.124 ± 0.035d.u., control group: 0.141 ± 0.028d.u., p < 0.05) were significantly reduced in PACG patients compared with control subjects. Significant decreases in GCL + IPL thickness (PACG group: 74.71 ± 39.56 μm, control group:113.61 ± 8.14 μm, p < 0.001) and CRT (PACG group: 254.49 ± 41.47 μm, control group:329.10 ± 18.57 μm, p < 0.001) were also observed in PACG eyes. There was no statistically significant correlation between the MPOD and GCL + IPL thickness (p = .639, p = .828). Conclusions MPOD was significantly lower in Chinese PACG patients than in the control group, potentially due to thinning of the GCL + IPL thickness. This study provides insights for the pathophysiology, assessment of PACG and potential guidance for lifestyle modifications.