Speckle-based Imaging Research Articles

Development of a nanometre scale X-ray speckle-based CT technique through the 3-D histological assessment of an acute respiratory distress syndrome model

The study of biological soft tissue structures at the micron scale details the function of healthy and pathological tissues, which is vital in the diagnosis and treatment of diseases. Speckle based X-ray phase contrast tomographic scans at a nanometer scale have the potential to thoroughly analyse such tissues in a quantitative and qualitative manner. Diamond light source, the UKs national synchrotron facility developed and refined a 1-D X-ray speckle-based imaging technique, referred to as Fly scan mode. This novel image acquisition technique was used to perform a rapid structural composition scan of rodent lung histology samples. The rodent samples were taken from healthy and Staphylococcus aureus induced acute respiratory distress syndrome models. The analysis and cross comparison of the fly scan method, absorption-based tomography and conventional histopathology H&E staining microscopy are discussed in this paper. This analysis and cross comparison outline the ways the speckle-based technique can be of benefit. These advantages include improved soft tissue contrast, 3-D volumetric rendering, segmentation of specific gross tissue structures, quantitative analysis of gross tissue volume. A further advantage is the analysis of cellular distribution throughout the volumetric rendering of the tissue sample. The study also details the current limitations of this technique and points to ways in which future work on this imaging modality may progress.

Wavefront shaping and imaging through a multimode hollow-core fiber

Multimode fibers recently emerged as compact minimally-invasive probes for high-resolution deep-tissue imaging. However, the commonly used silica fibers have a relatively low numerical aperture (NA) limiting the spatial resolution of a probe. On top of that, light propagation within the solid core generates auto-fluorescence and Raman background, which interferes with imaging. Here we propose to use a hollow-core fiber to solve these problems. We experimentally demonstrate spatial wavefront shaping at the multimode hollow-core fiber output with tunable high-NA. We demonstrate raster-scan and speckle-based compressive imaging through a multimode hollow-core fiber.

Speckle tracking phase-contrast computed tomography at an inverse Compton X-ray source.

Speckle-based X-ray imaging (SBI) is a phase-contrast method developed at and for highly coherent X-ray sources, such as synchrotrons, to increase the contrast of weakly absorbing objects. Consequently, it complements the conventional attenuation-based X-ray imaging. Meanwhile, attempts to establish SBI at less coherent laboratory sources have been performed, ranging from liquid metal-jet X-ray sources to microfocus X-ray tubes. However, their lack of coherence results in interference fringes not being resolved. Therefore, algorithms were developed which neglect the interference effects. Here, we demonstrate phase-contrast computed tomography employing SBI in a laboratory-setting with an inverse Compton X-ray source. In this context, we investigate and compare also the performance of the at synchrotron conventionally used phase-retrieval algorithms for SBI, unified modulated pattern analysis (UMPA) with a phase-retrieval method developed for low coherence systems (LCS). We successfully retrieve a full computed tomography in a phantom as well as in biological specimens, such as larvae of the greater wax moth (Galleria mellonella), a model system for studies of pathogens and infections. In this context, we additionally demonstrate quantitative phase-contrast computed tomography using SBI at a low coherent set-up.

Blood-inspired random bit generation using microfluidics system

The development of random number generators (RNGs) using speckle patterns is pivotal for secure encryption key generation, drawing from the recent statistical properties identified in speckle-based imaging. Speckle-based RNG systems generate a sequence of random numbers through the unpredictable and reproducible nature of speckle patterns, ensuring a source of randomness that is independent of algorithms. However, to guarantee their effectiveness and reliability, these systems demand a meticulous and rigorous approach. In this study, we present a blood-inspired RNG system with a microfluidics device, designed to generate random numbers at a rate of 5.5 MHz and a high-speed of 1250 fps. This process is achieved by directing a laser beam through a volumetric scattering medium to procure speckle patterns. Additionally, designed microfluidic device requires only a minimal blood sample of 5 µl to capture these speckle patterns effectively. After implementing the two-pass tuple-output von Neumann debiasing algorithm to counteract statistical biases, we utilized the randomness statistical test suite from the National Institute of Standards and Technology for validation. The generated numbers successfully passed these tests, ensuring their randomness and unpredictability. Our blood-inspired RNG, utilizing whole blood, offers a pathway for affordable, high-output applications in fields like encryption, computer security, and data protection.

Speckle-based imaging (SBI) applications with spectral photon counting detectors at the newly established OPTIMATO(OPTimal IMAging and TOmography) laboratory

Speckle-based imaging (SBI) is an advanced X-ray imaging technique that measures phase and dark-field signals, in addition to absorption signals. SBI uses random wavefront modulators to generate speckles and requires two images: one with a speckle pattern alone, and one with both the sample and speckles. SBI reconstruction algorithms retrieve three signals (transmission, refraction, and dark-field) by comparing the two images. In SBI, speckle visibility plays a crucial role in the retrieval of the three signals. When translating the technique from synchrotron sources to compact laboratory setups, the reduced coherence of the source and limitations in the available resolution yield lower speckle visibility, hampering the retrieval of phase and dark-field signals. In this context, direct-detection CdTe X-ray photon-counting detectors (XPCDs) provide an attractive solution, as they allow for a high detection efficiency and optimal spatial resolution enhancing speckle visibility. In this work, we present the newly established OPTIMATO (OPTimal IMAging and TOmography) laboratory for X-ray imaging hosted at the Elettra synchrotron (Trieste, Italy). The setup for SBI with resolutions up to 15 µm including an XPCD and a charge-integrating flat-panel detector (FPD) has been used to acquire SBI data. The main limiting factors when moving SBI applications from synchrotron facilities to compact laboratory setups are summarized. The advantages of XPCDs over FPDs are discussed by comparing the SBI images obtained using both detectors. The potential of the spectral decomposition approach via multi-threshold acquisitions using XPCDs is briefly introduced. The results shown in this work represent the first step toward the realization of a multimodal and multiresolution X-ray facility.

Multi-resolution X-ray phase-contrast and dark-field tomography of human cerebellum with near-field speckles.

In this study, we use synchrotron-based multi-modal X-ray tomography to examine human cerebellar tissue in three dimensions at two levels of spatial resolution (2.3 µm and 11.9 µm). We show that speckle-based imaging (SBI) produces results that are comparable to propagation-based imaging (PBI), a well-established phase-sensitive imaging method. The different SBI signals provide complementary information, which improves tissue differentiation. In particular, the dark-field signal aids in distinguishing tissues with similar average electron density but different microstructural variations. The setup's high resolution and the imaging technique's excellent phase sensitivity enabled the identification of different cellular layers and additionally, different cell types within these layers. We also correlated this high-resolution phase-contrast information with measured dark-field signal levels. These findings demonstrate the viability of SBI and the potential benefit of the dark-field modality for virtual histology of brain tissue.

Helical sample-stepping for faster speckle-based multi-modal tomography with the Unified Modulated Pattern Analysis (UMPA) model

Speckle-based imaging (SBI) is a multi-modal X-ray imaging technique that gives access to absorption, phase-contrast, and dark-field signals from a single dataset.However, it is often difficult to disentangle the different signals from a single measurement.Having complementary data obtained by repeating the scan under slightly varied conditions (multiframe approach) can significantly enhance the accuracy of signal extraction and, consequently, improve the overall quality of the final reconstruction.In order to retrieve the different channels, SBI relies on a reference pattern, generated by the addition of a wavefront marker in the beam (i.e., a sandpaper or gratings).Here, we show how a continuous helical acquisition can extend the field of view (FOV) and speed up the acquisition while maintaining a multiframe approach for the signal retrieval of a test object.

Comparing x-ray phase-contrast imaging using a Talbot array illuminator to propagation-based imaging for non-homogeneous biomedical samples

Phase-contrast computed tomography can visualize soft tissue samples with high contrast. At coherent sources, propagation-based imaging (PBI) techniques are among the most common, as they are easy to implement and produce high-resolution images. Their downside is a low degree of quantitative data due to simplifying assumptions of the sample properties in the reconstruction. These assumptions can be avoided, by using quantitative phase-contrast techniques as an alternative. However, these often compromise spatial resolution and require complicated setups. In order to overcome this limitation, we designed and constructed a new imaging setup using a 2D Talbot array illuminator as a wavefront marker and speckle-based imaging phase-retrieval techniques. We developed a post-processing chain that can compensate for wavefront marker drifts and that improves the overall sensitivity. By comparing two measurements of biomedical samples, we demonstrate that the spatial resolution of our setup is comparable to the one of PBI scans while being able to successfully image a sample that breaks the typical homogeneity assumption used in PBI.

Unified Modulation Pattern Analysis (UMPA) algorithm for 1D sensitive X-ray phase contrast imaging techniques

X-ray phase contrast imaging (XPCI) techniques are sensitive to refraction (differential-phase) and small-angle X-ray scattering (dark-field) signals, not measurable with conventional absorption imaging techniques. Among XPCI techniques, edge illumination (EI), grating interferometry (GI), and speckle-based imaging (SBI) make use of wavefront markers, such as absorbing masks with periodical apertures or random diffusers, to encode refraction and dark-field signals induced by the sample. The Unified Modulated Pattern Analysis (UMPA) provides an algorithmic solution to extract the transmission, refraction, and dark-field images from EI, GI, and SBI datasets where the wavefront marker is directly resolved by the employed detection system. In its original implementation, UMPA has been designed for XPCI techniques sensitive to refractions along two axes. This work presents a modified version of the algorithm to extend its applicability to all the existing XPCI techniques that use wavefront markers with sensitivity to refraction limited along one direction (UMPA-1D). The algorithm, written in C++ and Cython and parallelized with OpenMP, enables fast reconstruction times that are particularly convenient for large tomographic datasets. The validity of the UMPA-1D has been demonstrated using both simulated images and real acquisitions with an EI setup in beam-tracking mode.

Comparative analysis of speckle-based single-pixel imaging using uniform and non-redundant optical phased arrays.

An optical phased array (OPA) is a compact high-speed wavefront modulation device that is promising for next-generation optical sensing systems. In particular, speckle-based single-pixel imaging (SSPI) using OPA is an attractive scheme since precise tuning of optical phases is unnecessary. In this work, we present a comprehensive analysis of SSPI using an OPA with N phase shifters by comparing two classes of OPAs: uniformly spaced OPA (UOPA) and non-redundant OPA (NROPA). Through singular value decomposition analysis of the illumination patterns generated from the OPA, we clarify the theoretical limit of the imaging resolution for each case. As a result, the number of resolvable points can be as large as N 2-N+1 for the case of NROPA. This is in clear contrast to the case of UOPA, where the number of resolvable points can only be as large as 2N-1. Finally, imaging results of a test target are compared to study the impact of the array layout in OPA-based SSPI. Our work provides theoretical understanding of OPA-based SSPI and reveals the effectiveness of SSPI using NROPA.

X-ray directional dark-field imaging using Unified Modulated Pattern Analysis.

X-ray directional dark-field imaging is a recent technique that can reveal a sample’s small-scale structural properties which are otherwise invisible in a conventional imaging system. In particular, directional dark-field can detect and quantify the orientation of anisotropic structures. Here, we present an algorithm that allows for the extraction of a directional dark-field signal from X-ray speckle-based imaging data. The experimental setup is simple, as it requires only the addition of a diffuser to a full-field microscope setup. Sandpaper is an appropriate diffuser material in the hard x-ray regime. We propose an approach to extract the mean scattering width, directionality, and orientation from the recorded speckle images acquired with the technique. We demonstrate that our method can detect and quantify the orientation of fibres inside a carbon fibre reinforced polymer (CFRP) sample within one degree of accuracy and show how the accuracy depends on the number of included measurements. We show that the reconstruction parameters can be tuned to increase or decrease accuracy at the expense of spatial resolution.

Tuning Axial Resolution Independent of Lateral Resolution in a Computational Imaging System Using Bessel Speckles.

Speckle patterns are formed by random interferences of mutually coherent beams. While speckles are often considered as unwanted noise in many areas, they also formed the foundation for the development of numerous speckle-based imaging, holography, and sensing technologies. In the recent years, artificial speckle patterns have been generated with spatially incoherent sources using static and dynamic optical modulators for advanced imaging applications. In this report, a basic study has been carried out with Bessel distribution as the fundamental building block of the speckle pattern (i.e., speckle patterns formed by randomly interfering Bessel beams). In general, Bessel beams have a long focal depth, which in this scenario is counteracted by the increase in randomness enabling tunability of the axial resolution. As a direct imaging method could not be applied when there is more than one Bessel beam, an indirect computational imaging framework has been applied to study the imaging characteristics. This computational imaging process consists of three steps. In the first step, the point spread function (PSF) is calculated, which is the speckle pattern formed by the random interferences of Bessel beams. In the next step, the intensity distribution for an object is obtained by a convolution between the PSF and object function. The object information is reconstructed by processing the PSF and the object intensity distribution using non-linear reconstruction. In the computational imaging framework, the lateral resolution remained a constant, while the axial resolution improved when the randomness in the system was increased. Three-dimensional computational imaging with statistical averaging for different cases of randomness has been synthetically demonstrated for two test objects located at two different distances. The presented study will lead to a new generation of incoherent imaging technologies.

Epi-fluorescence imaging of the human brain through a multimode fiber

Visualization of the subcellular structures deep into the living brain is a major challenge in life science. Miniaturized microendoscopes allow for imaging of deep brain structures in vivo. Conventional approaches use gradient index (GRIN) microlenses, which unfortunately suffer from greater aberrations and restricted fields of view if they become smaller and less invasive. Multimode fiber based endoscopes offer minimal invasive access to deep tissue, and when combined with advanced wavefront engineering techniques, they provide high-resolution imaging. Here, we report auto-fluorescence human brain imaging through a single 50 μm-core multimode fiber probe with a numerical aperture of 0.22 via two approaches: raster-scan imaging by active wavefront shaping and speckle-based compressive imaging enabled by computational image recovery. The compressive imaging approach significantly decreases the acquisition time for an up to three times bigger area of interest while maintaining a high spatial resolution. Accumulation of age-related pigment lipofuscin in Alzheimer’s disease human brain has been visualized with sub-Nyquist–Shannon speed with an improvement of up to 18 times. The proposed technique offers fast, sensitive, and high-resolution endoscopic imaging through a single hair-thin fiber, which would be of broader interest in the fields of neuroimaging and (pre-)clinical research.

Multi-Modal X-ray Imaging and Analysis for Characterization of Urinary Stones

Backgound: The composition of stones formed in the urinary tract plays an important role in their management over time. The most common imaging method for the non-invasive evaluation of urinary stones is radiography and computed tomography (CT). However, CT is not very sensitive, and cannot differentiate between all critical stone types. In this study, we propose the application, and evaluate the potential, of a multi-modal (or multi-contrast) X-ray imaging technique called speckle-based imaging (SBI) to differentiate between various types of urinary stones. Methods: Three different stone samples were extracted from animal and human urinary tracts and examined in a laboratory-based speckle tracking setup. The results were discussed based on an X-ray diffraction analysis and a comparison with X-ray microtomography and grating-based interferometry. Results: The stones were classified through compositional analysis by X-ray diffraction. The multi-contrast images obtained using the SBI method provided detailed information about the composition of various urinary stone types, and could differentiate between them. X-ray SBI could provide highly sensitive and high-resolution characterizations of different urinary stones in the radiography mode, comparable to those by grating interferometry. Conclusions: This investigation demonstrated the capability of the SBI technique for the non-invasive classification of urinary stones through radiography in a simple and cost-effective laboratory setting. This opens the possibility for further studies concerning full-field in vivo SBI for the clinical imaging of urinary stones.

Real-time X-ray phase-contrast imaging using SPINNet—a speckle-based phase-contrast imaging neural network

X-ray phase-contrast imaging has become indispensable for visualizing samples with low absorption contrast. In this regard, speckle-based techniques have shown significant advantages in spatial resolution, phase sensitivity, and implementation flexibility compared with traditional methods. However, the computational cost associated with data inversion has hindered their wider adoption. By exploiting the power of deep learning, we developed a speckle-based phase-contrast imaging neural network (SPINNet) that significantly improves the imaging quality and boosts the phase retrieval speed by at least 2 orders of magnitude compared to existing methods. To achieve this performance, we combined SPINNet with a coded-mask-based technique, an enhanced version of the speckle-based method. Using this scheme, we demonstrate the simultaneous reconstruction of absorption and phase images on the order of 100 ms, where a traditional correlation-based analysis would take several minutes even with a cluster. In addition to significant improvement in speed, our experimental results show that the imaging and phase retrieval quality of SPINNet outperform existing single-shot speckle-based methods. Furthermore, we successfully demonstrate SPINNet application in x-ray optics metrology and 3D x-ray phase-contrast tomography. Our result shows that SPINNet could enable many applications requiring high-resolution and fast data acquisition and processing, such as in situ and in operando 2D and 3D phase-contrast imaging and real-time at-wavelength metrology and wavefront sensing.

X-ray speckle-based dark-field imaging of water transport in porous ceramics

The evaluation of liquid transport through porous ceramics are of high importance in numerous applications of these materials, ranging from chemical and physical filters to biomaterials. We present a proof-of-concept of the capability of speckle-based Xray dark-field imaging (XDFI) for studying the water transport through porous materials with high sensitivity and sub-pixel resolution in a laboratory. Speckle-based imaging (SBI) takes advantage of a simple and flexible setup, with only an additional and inexpensive textured mask, to provide complementary multi-contrast images. Porous ceramic samples with different pore size ranges were imaged in dry and different pure water-saturated states, via an X-ray speckle-tracking setup. The retrieved darkfield images revealed a high sensitivity to (1) the pore size range and to (2) the local water saturation degree. Independently of the pore size range, the dark-field signal decreased upon water saturation. Compared with previously reported laboratory-scale XDFI results for water transport through porous materials, the speckle-tracking approach allows achieving higher temporal and spatial resolutions, thus broadening the range of (water) transport processes which can be investigated without using any contrast agent.

Dark-field tomography of an attenuating object using intrinsic x-ray speckle tracking.

Purpose: We investigate how an intrinsic speckle tracking approach to speckle-based x-ray imaging is used to extract an object's effective dark-field (DF) signal, which is capable of providing object information in three dimensions. Approach: The effective DF signal was extracted using a Fokker-Planck type formalism, which models the deformations of illuminating reference beam speckles due to both coherent and diffusive scatter from the sample. Here, we assumed that (a)small-angle scattering fans at the exit surface of the sample are rotationally symmetric and (b)the object has both attenuating and refractive properties. The associated inverse problem of extracting the effective DF signal was numerically stabilized using a "weighted determinants" approach. Results: Effective DF projection images, as well as the DF tomographic reconstructions of the wood sample, are presented. DF tomography was performed using a filtered back projection reconstruction algorithm. The DF tomographic reconstructions of the wood sample provided complementary, and otherwise inaccessible, information to augment the phase contrast reconstructions, which were also computed. Conclusions: An intrinsic speckle tracking approach to speckle-based imaging can tomographically reconstruct an object's DF signal at a low sample exposure and with a simple experimental setup. The obtained DF reconstructions have an image quality comparable to alternative x-ray DF techniques.

High-Resolution Scanning Coded-Mask-Based X-ray Multi-Contrast Imaging and Tomography.

Near-field X-ray speckle tracking has been used in phase-contrast imaging and tomography as an emerging technique, providing higher contrast images than traditional absorption radiography. Most reported methods use sandpaper or membrane filters as speckle generators and digital image cross-correlation for phase reconstruction, which has either limited resolution or requires a large number of position scanning steps. Recently, we have proposed a novel coded-mask-based multi-contrast imaging (CMMI) technique for single-shot measurement with superior performance in efficiency and resolution compared with other single-shot methods. We present here a scanning CMMI method for the ultimate imaging resolution and phase sensitivity by using a coded mask as a high-contrast speckle generator, the flexible scanning mode, the adaption of advanced maximum-likelihood optimization to scanning data, and the multi-resolution analysis. Scanning CMMI can outperform other speckle-based imaging methods, such as X-ray speckle vector tracking, providing higher quality absorption, phase, and dark-field images with fewer scanning steps. Scanning CMMI is also successfully demonstrated in multi-contrast tomography, showing great potentials in high-resolution full-field imaging applications, such as in vivo biomedical imaging.

Implicit tracking approach for X-ray phase-contrast imaging with a random mask and a conventional system

X-ray phase contrast imaging (PCI) has shown great potential for clinical investigation of soft tissues. However, most of the existing X-ray PCI modalities require either a partially coherent source such as a synchrotron or complex setups that are barely compatible with low-dose and patient tomography. This work demonstrates the possibility to efficiently achieve PCI on a low coherence system with a conventional X-ray tube and a detector compatible with a clinical routine. This was accomplished by adapting the speckle-based imaging setup and the numerical phase retrieval processing methods to the low coherence and the low resolution of the experiment.

Evaluation of simulators for x-ray speckle-based phase contrast imaging

X-ray phase contrast imaging (PCI) denotes a group of highly sensitive imaging techniques that permits imaging at scales ranging from nanoscopic to the medical. Recently introduced, speckle-based imaging has seen a rapid development because of its experimental simplicity and its capability to retrieve the refraction, the scattering and the absorption of a sample using a conventional x-ray set-up. Precise simulation would permit to optimise the imaging setups for different applications, but until now works on simulation of x-ray speckle-based PCI have been very few. In this work we evaluate different simulation codes, based on Monte-Carlo, analytical ray-tracing and wave-optics Fresnel propagation. The simulation results are compared to both synchrotron and conventional imaging experiments to permits their validation. We obtain a strong similarity between simulated and experimental data. We discuss the validity and applicability of each approach.