Phase retrieval in X-ray phase-contrast imaging suitable for tomography

Res-U2Net: untrained deep learning for phase retrieval and image reconstruction

Conventional deep learning-based image reconstruction methods require a large amount of training data, which can be hard to obtain in practice. Untrained deep learning methods overcome this limitation by training a network to invert a physical model of the image formation process. Here we present a novel, to our knowledge, untrained Res-U2Net model for phase retrieval. We use the extracted phase information to determine changes in an object's surface and generate a mesh representation of its 3D structure. We compare the performance of Res-U2Net phase retrieval against UNet and U2Net using images from the GDXRAY dataset.

Integrating X-ray phase-contrast imaging and histology for comparative evaluation of breast tissue malignancies in virtual histology analysis

Detecting breast tissue alterations is essential for cancer diagnosis. However, inherent bidimensionality limits histological procedures' effectiveness in identifying these changes. Our study applies a 3D virtual histology method based on X-ray phase-contrast microtomography (PhC μ CT), performed at a synchrotron facility, to investigate breast tissue samples including different types of lesions, namely intraductal papilloma, micropapillary intracystic carcinoma, and invasive lobular carcinoma. One-to-one comparisons of X-ray and histological images explore the clinical potential of 3D X-ray virtual histology. Results show that PhC μ CT technique provides high spatial resolution and soft tissue sensitivity, while being non-destructive, not requiring a dedicated sample processing and being compatible with conventional histology. PhC μ CT can enhance the visualization of morphological characteristics such as stromal tissue, fibrovascular core, terminal duct lobular unit, stromal/epithelium interface, basement membrane, and adipocytes. Despite not reaching the (sub) cellular level, the three-dimensionality of PhC μ CT images allows to depict in-depth alterations of the breast tissues, potentially revealing pathologically relevant details missed by a single histological section. Compared to serial sectioning, PhC μ CT allows the virtual investigation of the sample volume along any orientation, possibly guiding the pathologist in the choice of the most suitable cutting plane. Overall, PhC μ CT virtual histology holds great promise as a tool adding to conventional histology for improving efficiency, accessibility, and diagnostic accuracy of pathological evaluation.

Framework to optimize fixed-length micro-CT systems for propagation-based phase-contrast imaging

A laboratory X-ray imaging system with a setup that closely resembles commercial micro-CT systems with a fixed source-to-detector distance of ∼90 cm is investigated for single distance propagation-based phase-contrast imaging and computed tomography (CT). The system had a constant source-to-detector distance, and the sample positions were optimized. Initially, a PTFE wire was imaged, both in 2D and 3D, to characterize fringe contrast and spatial resolution for different X-ray source settings and source-to-sample distances. The results were compared to calculated values based on theoretical models and to simulated (wave-optics based) results, with good agreement being found. The optimization of the imaging system is discussed. CT scans of two biological samples, a tissue-engineered esophageal scaffold and a rat heart, were then acquired at the optimum parameters, demonstrating that significant image quality improvements can be obtained with widely available components placed inside fixed-length cabinets through proper optimization of propagation-based phase-contrast.

Quantitative phase contrast X-ray tomography of aluminium metal matrix composite

The quantitative assessment of micro-structure and load-induced damages in Al-SiC metal matrix composites (MMC) is important for its design optimization, performance evaluation and structure-property correlation. X-ray Phase contrast micro-tomography is potentially used for evaluation of its 3 dimensional micro-structure manifested in the form of voids, cracks, embedded particles, and load-induced damages. However, the contrast between Al matrix and SiC particles is insufficient for their clear morphological identification and quantitative assessment. In the present study, we have proposed and applied single image-based phase retrieval as a pre-processing step to micro-tomography reconstruction for improved assessment of micro-structure and cohesion-induced damages in Al-SiC MMC. The advantages of applying different phase retrieval techniques in the enhancement of image quality and morphological quantification of SiC particles, pores and cohesion damages are discussed. It is observed that the Paganin method offers the best improvement in contrast to noise ratio for the measurement of SiC particles embedded in the Al matrix.

A high-throughput 3D X-ray histology facility for biomedical research and preclinical applications

Background

The University of Southampton, in collaboration with the University Hospital Southampton (UHS) NHS Foundation Trust and industrial partners, has been at the forefront of developing three-dimensional (3D) imaging workflows using X-ray microfocus computed tomography (μCT) -based technology. This article presents the outcomes of these endeavours and highlights the distinctive characteristics of a μCT facility tailored explicitly for 3D X-ray Histology, with a primary focus on applications in biomedical research and preclinical and clinical studies.

Methods

The UHS houses a unique 3D X-ray Histology (XRH) facility, offering a range of services to national and international clients. The facility employs specialised μCT equipment explicitly designed for histology applications, allowing whole-block XRH imaging of formalin-fixed and paraffin-embedded tissue specimens. It also enables correlative imaging by combining μCT imaging with other microscopy techniques, such as immunohistochemistry (IHC) and serial block-face scanning electron microscopy, as well as data visualisation, image quantification, and bespoke analysis.

Results

Over the past seven years, the XRH facility has successfully completed over 120 projects in collaboration with researchers from 60 affiliations, resulting in numerous published manuscripts and conference proceedings. The facility has streamlined the μCT imaging process, improving productivity and enabling efficient acquisition of 3D datasets.

Discussion & Conclusions

The 3D X-ray Histology (XRH) facility at UHS is a pioneering platform in the field of histology and biomedical imaging. To the best of our knowledge, it stands out as the world's first dedicated XRH facility, encompassing every aspect of the imaging process, from user support to data generation, analysis, training, archiving, and metadata generation. This article serves as a comprehensive guide for establishing similar XRH facilities, covering key aspects of facility setup and operation. Researchers and institutions interested in developing state-of-the-art histology and imaging facilities can utilise this resource to explore new frontiers in their research and discoveries.

X-ray Tomography Applied to Electrochemical Devices and Electrocatalysis

X-ray computed tomography (CT) is a nondestructive three-dimensional (3D) imaging technique used for studying morphological properties of porous and nonporous materials. In the field of electrocatalysis, X-ray CT is mainly used to quantify the morphology of electrodes and extract information such as porosity, tortuosity, pore-size distribution, and other relevant properties. For electrochemical systems such as fuel cells, electrolyzers, and redox flow batteries, X-ray CT gives the ability to study evolution of critical features of interest in ex situ, in situ, and operando environments. These include catalyst degradation, interface evolution under real conditions, formation of new phases (water and oxygen), and dynamics of transport processes. These studies enable more efficient device and electrode designs that will ultimately contribute to widespread decarbonization efforts.

Phase Retrieval-Based Phase-Contrast Imaging and CT of Living Zebrafish

Zebrafish are widely used as experimental animal models. They are small and move fast in the water. Real-time imaging of fast-moving zebrafish is a challenge, and it requires that the imaging technique has higher spatiotemporal resolution and penetration ability. The purpose of this study was to evaluate the feasibility of dynamic phase retrieval (PR)-based phase-contrast imaging (PCI) for real-time displaying of the breathing and swimming process in unanesthetized free-moving zebrafish, and to evaluate the feasibility of PR-based phase-contrast CT (PCCT) for visualizing the soft tissues in anesthetized living zebrafish. PR was performed using the phase-attenuation duality (PAD) method with the δ/β values (PAD property) of 100 and 1000 for dynamic PR-based PCI and PR-based PCCT, respectively. The contrast-to-noise ratio (CNR) was used for quantitatively assessing the visibility of the adipose tissue and muscle tissue. The skeleton and swim bladder chambers in fast-moving zebrafish were clearly shown. The dynamic processes of breathing and swimming were visibly recorded. The respiratory intensity and frequency and the movement flexibility of the zebrafish could be dynamically evaluated. By producing more obvious image contrast, PR-based PCCT clearly showed the adipose tissue and muscle tissue. The CNRs from PR-based PCCT were significantly higher than those from PR-free PCCT for both adipose tissue (9.256 ± 2.037 vs. 0.429 ± 0.426, p < 0.0001) and muscle tissue (7.095 ± 1.443 vs. 0.324 ± 0.267, p < 0.0001). Dynamic PR-based PCI holds the potential for investigating both morphological abnormalities and motor disorders. PR-based PCCT offers clear visualization and the potential for quantification of soft tissues in living zebrafish.

Investigating the robustness of a deep learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast measurements under laboratory conditions

Objective.Quantitative phase retrieval (QPR) in propagation-based x-ray phase contrast imaging of heterogeneous and structurally complicated objects is challenging under laboratory conditions due to partial spatial coherence and polychromaticity. A deep learning-based method (DLBM) provides a nonlinear approach to this problem while not being constrained by restrictive assumptions about object properties and beam coherence. The objective of this work is to assess a DLBM for its applicability under practical scenarios by evaluating its robustness and generalizability under typical experimental variations.Approach.Towards this end, an end-to-end DLBM was employed for QPR under laboratory conditions and its robustness was investigated across various system and object conditions. The robustness of the method was tested via varying propagation distances and its generalizability with respect to object structure and experimental data was also tested.Main results.Although the end-to-end DLBM was stable under the studied variations, its successful deployment was found to be affected by choices pertaining to data pre-processing, network training considerations and system modeling.Significance.To our knowledge, we demonstrated for the first time, the potential applicability of an end-to-end learning-based QPR method, trained on simulated data, to experimental propagation-based x-ray phase contrast measurements acquired under laboratory conditions with a commercial x-ray source and a conventional detector. We considered conditions of polychromaticity, partial spatial coherence, and high noise levels, typical to laboratory conditions. This work further explored the robustness of this method to practical variations in propagation distances and object structure with the goal of assessing its potential for experimental use. Such an exploration of any DLBM (irrespective of its network architecture) before practical deployment provides an understanding of its potential behavior under experimental settings.

Image quality and scan time optimisation for in situ phase contrast x-ray tomography of the intervertebral disc

In-line phase contrast synchrotron tomography combined with in situ mechanical loading enables the characterisation of soft tissue micromechanics via digital volume correlation (DVC) within whole organs. Optimising scan time is important for reducing radiation dose from multiple scans and to limit sample movement during acquisition. Also, although contrasted edges provided by in-line phase contrast tomography of soft tissues are useful for DVC, the effect of phase contrast imaging on its accuracy has yet to be investigated. Due to limited time at synchrotron facilities, scan parameters are often decided during imaging and their effect on DVC accuracy is not fully understood. Here, we used previously published data of intervertebral disc phase contrast tomography to evaluate the influence of i) fibrous image texture, ii) number of projections, iii) tomographic reconstruction method, and iv) phase contrast propagation distance on DVC results. A greater understanding of how image texture influences optimal DVC tracking was obtained by visualising objective function mapping, enabling tracking inaccuracies to be identified. When reducing the number of projections, DVC was minimally affected by image high frequency noise but with a compromise in accuracy. Iterative reconstruction methods improved image signal-to-noise and consequently significantly lowered DVC displacement uncertainty. Propagation distance was shown to affect DVC accuracy. Consistent DVC results were achieved within a propagation distance range which provided contrast to the smallest scale features, where; too short a distance provided insufficient features to track, whereas too long led to edge effect inconsistencies, particularly at greater deformations. Although limited to a single sample type and image setup, this study provides general guidelines for future investigations when optimising image quality and scan times for in situ phase contrast x-ray tomography of fibrous connective tissues.

Cycloidal-spiral sampling for three-modal x-ray CT flyscans with two-dimensional phase sensitivity

We present a flyscan compatible acquisition scheme for three-modal X-Ray Computed Tomography (CT) with two-dimensional phase sensitivity. Our approach is demonstrated using a "beam tracking" setup, through which a sample's attenuation, phase (refraction) and scattering properties can be measured from a single frame, providing three complementary contrast channels. Up to now, such setups required the sample to be stepped at each rotation angle to sample signals at an adequate rate, to prevent resolution losses, anisotropic resolution, and under-sampling artefacts. However, the need for stepping necessitated a step-and-shoot implementation, which is affected by motors' overheads and increases the total scan time. By contrast, our proposed scheme, by which continuous horizontal and vertical translations of the sample are integrated with its rotation (leading to a "cycloidal-spiral" trajectory), is fully compatible with continuous scanning (flyscans). This leads to greatly reduced scan times while largely preserving image quality and isotropic resolution.

Fast algorithms for nonlinear and constrained phase retrieval in near-field X-ray holography based on Tikhonov regularization

Based on phase retrieval, lensless coherent imaging and in particular holography offers quantitative phase and amplitude images. This is of particular importance for spectral ranges where suitable lenses are challenging, such as for hard x-rays. Here, we propose a phase retrieval approach for inline x-ray holography based on Tikhonov regularization applied to the full nonlinear forward model of image formation. The approach can be seen as a nonlinear generalization of the well-established contrast transfer function (CTF) reconstruction method. While similar methods have been proposed before, the current work achieves nonlinear, constrained phase retrieval at competitive computation times. We thus enable high-throughput imaging of optically strong objects beyond the scope of CTF. Using different examples of inline holograms obtained from illumination by a x-ray waveguide-source, we demonstrate superior image quality even for samples which do not obey the assumption of a weakly varying phase. Since the presented approach does not rely on linearization, we expect it to be well suited also for other probes such as visible light or electrons, which often exhibit strong phase interaction.

Direct Conversion X-ray Detector with Micron-Scale Pixel Pitch for Edge-Illumination and Propagation-Based X-ray Phase-Contrast Imaging

In this work, we investigate the potential of employing a direct conversion integration mode X-ray detector with micron-scale pixels in two different X-ray phase-contrast imaging (XPCi) configurations, propagation-based (PB) and edge illumination (EI). Both PB-XPCi and EI-XPCi implementations are evaluated through a wave optics model-numerically simulated in MATLAB-and are compared based on their contrast, edge-enhancement, visibility, and dose efficiency characteristics. The EI-XPCi configuration, in general, demonstrates higher performance compared to PB-XPCi, considering a setup with the same X-ray source and detector. However, absorption masks quality (thickness of X-ray absorption material) and environmental vibration effect are two potential challenges for EI-XPCi employing a detector with micron-scale pixels. Simulation results confirm that the behavior of an EI-XPCi system employing a high-resolution detector is susceptible to its absorption masks thickness and misalignment. This work demonstrates the potential and feasibility of employing a high-resolution direct conversion detector for phase-contrast imaging applications where higher dose efficiency, higher contrast images, and a more compact imaging system are of interest.

Morphological variations to a ptychographic algorithm

Ptychography is a technique widely used in microscopy for achieving high-resolution imaging. This method relies on computational processing of images gathered from diffraction patterns produced by several partial illuminations of a sample. We numerically studied the effect of using different shapes for illuminating the aforementioned sample: convex shapes, such as circles and regular polygons, and unconnected shapes that resemble a QR code. Our results suggest that the use of unconnected shapes seems to outperform convex shapes in terms of convergence and, in some cases, accuracy.

Suppressing multi-material and streak artifacts with an accelerated 3D iterative image reconstruction algorithm for in-line X-ray phase-contrast computed tomography

In-line X-ray phase-contrast computed tomography typically contains two independent procedures: phase retrieval and computed tomography reconstruction, in which multi-material and streak artifacts are two important problems. To address these problems simultaneously, an accelerated 3D iterative image reconstruction algorithm is proposed. It merges the above-mentioned two procedures into one step, and establishes the data fidelity term in raw projection domain while introducing 3D total variation regularization term in image domain. Specifically, a transport-of-intensity equation (TIE)-based phase retrieval method is updated alternately for different areas of the multi-material sample. Simulation and experimental results validate the effectiveness and efficiency of the proposed algorithm.

Improving spatial resolution with an edge-enhancement model for low-dose propagation-based X-ray phase-contrast computed tomography

Propagation-based X-ray phase-contrast computed tomography (PB-PCCT) has been increasingly popular for distinguishing low contrast tissues. Phase retrieval is an important step to quantitatively obtain the phase information before the tomographic reconstructions, while typical phase retrieval methods in PB-PCCT, such as homogenous transport of intensity equation (TIE-Hom), are essentially low-pass filters and thus improve the signal to noise ratio at the expense of the reduced spatial resolution of the reconstructed image. To improve the reconstructed spatial resolution, measured phase contrast projections with high edge enhancement and the phase projections retrieved by TIE-Hom were weighted summed and fed into an iterative tomographic algorithm within the framework of the adaptive steepest descent projections onto convex sets (ASD-POCS), which was employed for suppressing the image noise in low dose reconstructions because of the sparse-view scanning strategy or low exposure time for single phase contrast projection. The merging strategy decreases the accuracy of the linear model of PB-PCCT and would finally lead to the reconstruction failure in iterative reconstructions. Therefore, the additive median root prior is also introduced in the algorithm to partly increase the model accuracy. The reconstructed spatial resolution and noise performance can be flexibly balanced by a pair of antagonistic hyper-parameters. Validations were performed by the established phase-contrast Feldkamp-Davis-Kress, phase-retrieved Feldkamp-Davis-Kress, conventional ASD-POCS and the proposed enhanced ASD-POCS with a numerical phantom dataset and experimental biomaterial dataset. Simulation results show that the proposed algorithm outperforms the conventional ASD-POCS in spatial evaluation assessments such as root mean square error (a ratio of 9.78%), contrast to noise ratio (CNR) (a ratio of 7.46%), and also frequency evaluation assessments such as modulation transfer function (a ratio of 66.48% of MTF_50% (50% MTF value)), noise power spectrum (a ratio of 35.25% of f_50% (50% value of the Nyquist frequency)) and noise equivalent quanta (1-2 orders of magnitude at high frequencies). Experimental results again confirm the superiority of proposed strategy relative to the conventional one in terms of edge sharpness and CNR (an average increase of 67.35%).

Dual-energy phase retrieval algorithm for inline phase sensitive x-ray imaging system

Phase retrieval is vital for quantitative x-ray phase contrast imaging. This work presents an iterative method to simultaneously retrieve the x-ray absorption and phase images from a single x-ray exposure. The proposed approach uses the photon-counting detectors' energy-resolving capability in providing multiple spectrally resolved phase contrast images from a single x-ray exposure. The retrieval method is derived, presented, and experimentally tested with a multi-material phantom in an inline phase contrast imaging setup. By separating the contributions of photoelectric absorption and Compton scattering to the attenuation, the authors divide the phase contrast image into two portions, the attenuation map arises from photoelectric absorption and a pseudo phase contrast image generated by electron density. This way one can apply the Phase Attenuation Dualiby (PAD) algorithm and Fresnel propagation for the iteration. The retrieval results from the experimental images show that this iterative method is fast, accurate, robust against noise, and thus yields noticeable enhancement in contrast to noise ratios.

Deep learning-based single-shot phase retrieval algorithm for surface plasmon resonance microscope based refractive index sensing application

A deep learning algorithm for single-shot phase retrieval under a conventional microscope is proposed and investigated. The algorithm has been developed using the context aggregation network architecture; it requires a single input grayscale image to predict an output phase profile through deep learning-based pattern recognition. Surface plasmon resonance imaging has been employed as an example to demonstrate the capability of the deep learning-based method. The phase profiles of the surface plasmon resonance phenomena have been very well established and cover ranges of phase transitions from 0 to 2π rad. We demonstrate that deep learning can be developed and trained using simulated data. Experimental validation and a theoretical framework to characterize and quantify the performance of the deep learning-based phase retrieval method are reported. The proposed deep learning-based phase retrieval performance was verified through the shot noise model and Monte Carlo simulations. Refractive index sensing performance comparing the proposed deep learning algorithm and conventional surface plasmon resonance measurements are also discussed. Although the proposed phase retrieval-based algorithm cannot achieve a typical detection limit of 10^-7 to 10^-8 RIU for phase measurement in surface plasmon interferometer, the proposed artificial-intelligence-based approach can provide at least three times lower detection limit of 4.67 × 10^-6 RIU compared to conventional intensity measurement methods of 1.73 × 10^-5 RIU for the optical energy of 2500 pJ with no need for sophisticated optical interferometer instrumentation.

Development and preclinical evaluation of a patient-specific high energy x-ray phase sensitive breast tomosynthesis system

BACKGROUND

This article reports the first x-ray phase sensitive breast tomosynthesis (PBT) system that is aimed for direct translation to clinical practice for the diagnosis of breast cancer.

PURPOSE

To report the preclinical evaluation and comparison of the newly built PBT system with a conventional digital breast tomosynthesis (DBT) system.

METHODS AND MATERIALS

The PBT system is developed based on a comprehensive inline phase contrast theoretical model. The system consists of a polyenergetic microfocus x-ray source and a flat panel detector mounted on an arm that is attached to a rotating gantry. It acquires nine projections over a 15° angular span in a stop-and-shoot manner. A dedicated phase retrieval algorithm is integrated with a filtered back-projection method that reconstructs tomographic slices. The American College of Radiology (ACR) accreditation phantom, a contrast detail (CD) phantom and mastectomy tissue samples were imaged at the same glandular dose levels by both the PBT and a standard of care DBT system for image quality characterizations and comparisons.

RESULTS

The PBT imaging scores with the ACR phantom are in good to excellent range and meet the quality assurance criteria set by the Mammography Quality Standard Act. The CD phantom image comparison and associated statistical analyses from two-alternative forced-choice reader studies confirm the improvement offered by the PBT system in terms of contrast resolution, spatial resolution, and conspicuity. The artifact spread function (ASF) analyses revealed a sizable lateral spread of metal artifacts in PBT slices as compared to DBT slices. Signal-to-noise ratio values for various inserts of the ACR and CD phantoms further validated the superiority of the PBT system. Mastectomy sample images acquired by the PBT system showed a superior depiction of microcalcifications vs the DBT system.

CONCLUSION

The PBT imaging technology can be clinically employed for improving the accuracy of breast cancer screening and diagnosis.

X-ray Dark-Field Imaging (XDFI)-a Promising Tool for 3D Virtual Histopathology

X-ray dark-field imaging (XDFI) utilizing a thin silicon crystal under Laue case enables visualizing three-dimensional (3D) morphological alterations of human tissue. XDFI uses refraction-contrast derived from phase shift rather than absorption as the main X-ray image contrast source to render 2D and 3D images of tissue specimens in unprecedented detail. The unique features of XDFI are its extremely high sensitivity (approximately 1000:1 compared to absorption for soft tissues under X-ray energy of around 20 keV, theoretically) and excellent resolution (8.5 μm) without requiring contrast medium or staining. Thus, XDFI-computed tomography can generate 3D virtual histological images equivalent to those of stained histological sections pathologists observe under low-power light microscopy as far as organs and tissues selected as samples in preliminary studies. This paper reviews the fundamental principles and the potential of XDFI, describes two optical setups for XDFI with examples, illustrates features of XDFI that are salient for histopathology, and presents XDFI examples of refraction-contrast images of atherosclerotic plaques, musculoskeletal tissue, neuronal tissue, and breast cancer specimens. Availability of this X-ray imaging in routine histopathological evaluations of tissue specimens would help guide clinical decision making by highlighting suspicious areas in unstained, thick sections for further sampling and analysis using conventional histopathological techniques. XDFI is a promising tool for 3D virtual histopathology.

FleXCT: a flexible X-ray CT scanner with 10 degrees of freedom

Laboratory based X-ray micro-CT is a non-destructive testing method that enables three dimensional visualization and analysis of the internal and external morphology of samples. Although a wide variety of commercial scanners exist, most of them are limited in the number of degrees of freedom to position the source and detector with respect to the object to be scanned. Hence, they are less suited for industrial X-ray imaging settings that require advanced scanning modes, such as laminography, conveyor belt scanning, or time-resolved imaging (4DCT). We introduce a new X-ray scanner FleXCT that consists of a total of ten motorized axes, which allow a wide range of non-standard XCT scans such as tiled and off-centre scans, laminography, helical tomography, conveyor belt, dynamic zooming, and X-ray phase contrast imaging. Additionally, a new software tool 'FlexRayTools' was created that enables reconstruction of non-standard XCT projection data of the FleXCT instrument using the ASTRA Toolbox, a highly efficient and open source set of tools for tomographic projection and reconstruction.

A computational platform for the virtual unfolding of Herculaneum Papyri

Ancient Herculaneum papyrus scrolls, hopelessly charred in the 79 A.D. Vesuvius eruption, contain valuable writings of the Greek philosophers of the day, including works of the Epicurean Philodemus. X-ray phase contrast tomography has recently begun unlocking their secrets. However, only small portions of the text hidden inside the scroll have been recover. One of the challenging tasks in Herculaneum papyri investigation is their virtual unfolding because of their highly complicated structure and three-dimensional arrangement. Although this procedure is feasible, problems in segmentation and flattening hinder the unrolling of a large portion of papyrus. We propose a computational platform for the virtual unfolding procedure, and we show the results of its application on two Herculaneum papyrus fragments. This work paves the way to a comprehensive survey and to further interpretation of larger portions of text hidden inside the carbonized Herculaneum papyri.

Quantitative phase retrieval with low photon counts using an energy resolving quantum detector

X-ray phase contrast imaging (PCI) combined with phase retrieval has the potential to improve soft-material visibility and discrimination. This work examined the accuracy, image quality gains, and robustness of a spectral phase retrieval method proposed by our group. Spectroscopic PCI measurements of a physical phantom were obtained using state-of-the-art photon-counting detectors in combination with a polychromatic x-ray source. The phantom consisted of four poorly attenuating materials. Excellent accuracy was demonstrated in simultaneously retrieving the complete refractive properties (photoelectric absorption, attenuation, and phase) of these materials. Approximately 10 times higher SNR was achieved in retrieved images compared to the original PCI intensity image. These gains are also shown to be robust against increasing quantum noise, even for acquisition times as low as 1 s with a low-flux microfocus x-ray tube (average counts of 250 photons/pixels). We expect that this spectral phase retrieval method, adaptable to several PCI geometries, will allow significant dose reduction and improved material discrimination in clinical and industrial x-ray imaging applications.

Material Decomposition Using Spectral Propagation-Based Phase-Contrast X-Ray Imaging

Material decomposition in X-ray imaging uses the energy-dependence of attenuation to digitally decompose an object into specific constituent materials, generally at the cost of enhanced image noise. Propagation-based X-ray phase-contrast imaging is a developing technique that can be used to reduce image noise, in particular from weakly attenuating objects. In this paper, we combine spectral phase-contrast imaging with material decomposition to both better visualize weakly attenuating features and separate them from overlying objects in radiography. We derive an algorithm that performs both tasks simultaneously and verify it against numerical simulations and experimental measurements of ideal two-component samples composed of pure aluminum and poly(methyl methacrylate). Additionally, we showcase first imaging results of a rabbit kitten's lung. The attenuation signal of a thorax, in particular, is dominated by the strongly attenuating bones of the ribcage. Combined with the weak soft tissue signal, this makes it difficult to visualize the fine anatomical structures across the whole lung. In all cases, clean material decomposition was achieved, without residual phase-contrast effects, from which we generate an un-obstructed image of the lung, free of bones. Spectral propagation-based phase-contrast imaging has the potential to be a valuable tool, not only in future lung research, but also in other systems for which phase-contrast imaging in combination with material decomposition proves to be advantageous.

Optimizing and applying high-resolution, in-line laboratory phase-contrast X-ray imaging for low-density material samples

In-line, or propagation-based phase-contrast X-ray imaging (PBI) is an attractive alternative to the attenuation-based modality for low-density, soft samples showing low attenuation contrast. With the growing availability of micro- and nano-focus X-ray tubes, the method is increasingly applied in the laboratory. Here, we discuss the technique and demonstrate its advantages for selected low-density, low attenuation material samples using a lab-based micro- and nano-computed tomography systems Easytom XL Ultra, providing micron and sub-micron range resolution PBI images. We demonstrate a multi-step optimization of the lab-based PBI technique on our scanner that includes choosing the optimal detector-source hardware combination available in the setup, then optimizing the imaging geometry and finally the phase retrieval process through a parametric study. We point out and elaborate on the effect of noise correlation and texturing due to phase retrieval. We demonstrate the overall benefits of using the phase image and the phase retrieval for the selected samples such as improved image quality, increased contrast-to-noise ratio while only marginally influencing the spatial resolution. The improvement in image quality also enables further image processing steps for detailed structural analysis of the samples, which would be much more complicated if not impossible based on the transmission image.

Innovative high-resolution microCT imaging of animal brain vasculature

Analysis of the angioarchitecture and quantification of the conduit vessels and microvasculature is of paramount importance for understanding the physiological and pathological processes within the central nervous system (CNS). Most of the available in vivo imaging methods lack penetration depth and/or resolution. Some ex vivo methods may provide better resolution, but are mainly destructive, as they are designed for imaging the CNS tissues after their removal from the skull or vertebral column. The removal procedure inevitably alters the in situ relations of the investigated structures and damages the dura mater and leptomeninges. µAngiofil, a polymer-based contrast agent, permits a qualitatively novel postmortem microangio-computed tomography (microangioCT) approach with excellent resolution and, therefore, visualization of the smallest brain capillaries. The datasets obtained empower a rather straightforward quantitative analysis of the vascular tree, including the microvasculature. The µAngiofil has an excellent filling capacity as well as a radio-opacity higher than the one of bone tissue, which allows imaging the cerebral microvasculature even within the intact skull or vertebral column. This permits in situ visualization and thus investigation of the dura mater and leptomeningeal layers as well as their blood supply in their original geometry. Moreover, the methodology introduced here permits correlative approaches, i.e., microangioCT followed by classical histology, immunohistochemistry and even electron microscopy. The experimental approach presented here makes use of common desktop microCT scanners, rendering it a promising everyday tool for the evaluation of the (micro)vasculature of the central nervous system in preclinical and basic research.

Functional lung imaging with synchrotron radiation: Methods and preclinical applications

Many lung disease processes are characterized by structural and functional heterogeneity that is not directly appreciable with traditional physiological measurements. Experimental methods and lung function modeling to study regional lung function are crucial for better understanding of disease mechanisms and for targeting treatment. Synchrotron radiation offers useful properties to this end: coherence, utilized in phase-contrast imaging, and high flux and a wide energy spectrum which allow the selection of very narrow energy bands of radiation, thus allowing imaging at very specific energies. K-edge subtraction imaging (KES) has thus been developed at synchrotrons for both human and small animal imaging. The unique properties of synchrotron radiation extend X-ray computed tomography (CT) capabilities to quantitatively assess lung morphology, and also to map regional lung ventilation, perfusion, inflammation and biomechanical properties, with microscopic spatial resolution. Four-dimensional imaging, allows the investigation of the dynamics of regional lung functional parameters simultaneously with structural deformation of the lung as a function of time. This review summarizes synchrotron radiation imaging methods and overviews examples of its application in the study of disease mechanisms in preclinical animal models, as well as the potential for clinical translation both through the knowledge gained using these techniques and transfer of imaging technology to laboratory X-ray sources.

Neutron sub-micrometre tomography from scattering data

Neutrons are valuable probes for various material samples across many areas of research. Neutron imaging typically has a spatial resolution of larger than 20 µm, whereas neutron scattering is sensitive to smaller features but does not provide a real-space image of the sample. A computed-tomography technique is demonstrated that uses neutron-scattering data to generate an image of a periodic sample with a spatial resolution of ∼300 nm. The achieved resolution is over an order of magnitude smaller than the resolution of other forms of neutron tomography. This method consists of measuring neutron diffraction using a double-crystal diffractometer as a function of sample rotation and then using a phase-retrieval algorithm followed by tomographic reconstruction to generate a map of the sample's scattering-length density. Topological features found in the reconstructions are confirmed with scanning electron micrographs. This technique should be applicable to any sample that generates clear neutron-diffraction patterns, including nanofabricated samples, biological membranes and magnetic materials, such as skyrmion lattices.

Evaluation of the Weighted Mean X-ray Energy for an Imaging System Via Propagation-Based Phase-Contrast Imaging

For imaging events of extremely short duration, like shock waves or explosions, it is necessary to be able to image the object with a single-shot exposure. A suitable setup is given by a laser-induced X-ray source such as the one that can be found at GSI (Helmholtzzentrum für Schwerionenforschung GmbH) in Darmstadt (Society for Heavy Ion Research), Germany. There, it is possible to direct a pulse from the high-energy laser Petawatt High Energy Laser for Heavy Ion eXperiments (PHELIX) on a tungsten wire to generate a picosecond polychromatic X-ray pulse, called backlighter. For grating-based single-shot phase-contrast imaging of shock waves or exploding wires, it is important to know the weighted mean energy of the X-ray spectrum for choosing a suitable setup. In propagation-based phase-contrast imaging the knowledge of the weighted mean energy is necessary to be able to reconstruct quantitative phase images of unknown objects. Hence, we developed a method to evaluate the weighted mean energy of the X-ray backlighter spectrum using propagation-based phase-contrast images. In a first step wave-field simulations are performed to verify the results. Furthermore, our evaluation is cross-checked with monochromatic synchrotron measurements with known energy at Diamond Light Source (DLS, Didcot, UK) for proof of concepts.

Model-Based Iterative Reconstruction for Propagation-Based Phase-Contrast X-Ray CT including Models for the Source and the Detector

Propagation-based phase-contrast X-ray computed tomography is a valuable tool for high-resolution visualization of biological samples, giving distinct improvements in terms of contrast and dose requirements compared to conventional attenuation-based computed tomography. Due to its ease of implementation and advances in laboratory X-ray sources, this imaging technique is increasingly being transferred from synchrotron facilities to laboratory environments. This however poses additional challenges, such as the limited spatial coherence and flux of laboratory sources, resulting in worse resolution and higher noise levels. Here we extend a previously developed iterative reconstruction algorithm for this imaging technique to include models for the reduced spatial coherence and the signal spreading of efficient scintillator-based detectors directly into the physical forward model. Furthermore, we employ a noise model which accounts for the full covariance statistics of the image formation process. In addition, we extend the model describing the interference effects such that it now matches the formalism of the widely-used single-material phase-retrieval algorithm, which is based on the sample-homogeneity assumption. We perform a simulation study as well as an experimental study at a laboratory inverse Compton source and compare our approach to the conventional analytical approaches. We find that the modeling of the source and the detector inside the physical forward model can tremendously improve the resolution at matched noise levels and that the modeling of the covariance statistics reduces overshoots (i.e. incorrect increase / decrease in sample properties) at the sample edges significantly.

Towards Monte Carlo simulation of X-ray phase contrast using GATE

We describe the first developments towards a Monte Carlo X-ray phase contrast imaging simulator for the medical imaging and radiotherapy simulation software GATE. Phase contrast imaging is an imaging modality taking advantage of the phase shift of X-rays. This modality produces images with a higher sensitivity than conventional, attenuation based imaging. As the first developments towards Monte Carlo phase contrast simulation, we implemented a Monte Carlo process for the refraction and total reflection of X-rays, as well as an analytical wave optics approach for generating Fresnel diffraction patterns. The implementation is validated against data acquired using a laboratory X-ray tomography system. The overall agreement between the simulations and the data is encouraging, which motivates further development of Monte Carlo based simulation of X-ray phase contrast imaging. These developments have been released in GATE version 8.2.

A phase-retrieval toolbox for X-ray holography and tomography

Propagation-based phase-contrast X-ray imaging is by now a well established imaging technique, which - as a full-field technique - is particularly useful for tomography applications. Since it can be implemented with synchrotron radiation and at laboratory micro-focus sources, it covers a wide range of applications. A limiting factor in its development has been the phase-retrieval step, which was often performed using methods with a limited regime of applicability, typically based on linearization. In this work, a much larger set of algorithms, which covers a wide range of cases (experimental parameters, objects and constraints), is compiled into a single toolbox - the HoloTomoToolbox - which is made publicly available. Importantly, the unified structure of the implemented phase-retrieval functions facilitates their use and performance test on different experimental data.

Three dimensions, two microscopes, one code: Automatic differentiation for x-ray nanotomography beyond the depth of focus limit

Conventional tomographic reconstruction algorithms assume that one has obtained pure projection images, involving no within-specimen diffraction effects nor multiple scattering. Advances in x-ray nanotomography are leading toward the violation of these assumptions, by combining the high penetration power of x-rays, which enables thick specimens to be imaged, with improved spatial resolution that decreases the depth of focus of the imaging system. We describe a reconstruction method where multiple scattering and diffraction effects in thick samples are modeled by multislice propagation and the 3D object function is retrieved through iterative optimization. We show that the same proposed method works for both full-field microscopy and for coherent scanning techniques like ptychography. Our implementation uses the optimization toolbox and the automatic differentiation capability of the open-source deep learning package TensorFlow, demonstrating a straightforward way to solve optimization problems in computational imaging with flexibility and portability.

Quantitative phase contrast imaging of a shock-wave with a laser-plasma based X-ray source

X-ray phase contrast imaging (XPCI) is more sensitive to density variations than X-ray absorption radiography, which is a crucial advantage when imaging weakly-absorbing, low-Z materials, or steep density gradients in matter under extreme conditions. Here, we describe the application of a polychromatic X-ray laser-plasma source (duration ~0.5 ps, photon energy >1 keV) to the study of a laser-driven shock travelling in plastic material. The XPCI technique allows for a clear identification of the shock front as well as of small-scale features present during the interaction. Quantitative analysis of the compressed object is achieved using a density map reconstructed from the experimental data.

Two improved defocus quantitative phase imaging methods: discussion

Multifilter phase imaging with partially coherent light (MFPI-PC) and phase optical transfer function recovery (POTFR) are two viable defocus-based, two-dimensional quantitative phase imaging (QPI) methods. While both methods use transfer function inversion, MFPI-PC is based on the in-focus intensity derivative, while POTFR is based on the intensity difference between symmetrically defocused images. This paper compares and contrasts MFPI-PC and POTFR. Six disadvantages (five in MFPI-PC and one in POTFR) are identified. Improvement strategies to overcome each of the six shortcomings are identified and implemented, and both methods are shown to be clearly improved. The revised MFPI-PC is shown to be more accurate than the original MFPI-PC and generally more accurate than the revised POTFR. The revised POTFR is shown to be inherently faster than the original POTFR and also slightly faster than the revised MFPI-PC.

Advanced X-ray CT scanning can boost tree ring research for earth system sciences

BACKGROUND AND AIMS

Tree rings, as archives of the past and biosensors of the present, offer unique opportunities to study influences of the fluctuating environment over decades to centuries. As such, tree-ring-based wood traits are capital input for global vegetation models. To contribute to earth system sciences, however, sufficient spatial coverage is required of detailed individual-based measurements, necessitating large amounts of data. X-ray computed tomography (CT) scanning is one of the few techniques that can deliver such data sets.

METHODS

Increment cores of four different temperate tree species were scanned with a state-of-the-art X-ray CT system at resolutions ranging from 60 μm down to 4.5 μm, with an additional scan at a resolution of 0.8 μm of a splinter-sized sample using a second X-ray CT system to highlight the potential of cell-level scanning. Calibration-free densitometry, based on full scanner simulation of a third X-ray CT system, is illustrated on increment cores of a tropical tree species.

KEY RESULTS

We show how multiscale scanning offers unprecedented potential for mapping tree rings and wood traits without sample manipulation and with limited operator intervention. Custom-designed sample holders enable simultaneous scanning of multiple increment cores at resolutions sufficient for tree ring analysis and densitometry as well as single core scanning enabling quantitative wood anatomy, thereby approaching the conventional thin section approach. Standardized X-ray CT volumes are, furthermore, ideal input imagery for automated pipelines with neural-based learning for tree ring detection and measurements of wood traits.

CONCLUSIONS

Advanced X-ray CT scanning for high-throughput processing of increment cores is within reach, generating pith-to-bark ring width series, density profiles and wood trait data. This would allow contribution to large-scale monitoring and modelling efforts with sufficient global coverage.

Investigation on the Dependency of Phase Retrieval Accuracy Versus Edge Enhancement to the Noise Ratio of X-ray Propagation-Based Phase-Contrast Imaging

Phase retrieval is necessary for propagation-based phase-contrast imaging (PB-PCI). Arhatari established a model for predicting the impact of the sample-to-detector distance and the system noise on the phase retrieval performance. We have extended Arhatari's model to account for the parameters of excessive source size, finite detector resolution, and geometrical magnification for more practical cases. However, there exist interaction effects among these parameters resulting in difficulty of predicting the phase retrieval performance. In this study, we found that optimizing the trade-off among these parameters for phase retrieval is consistent with the improvement of edge enhancement to noise ratio (EE/N) in the "forward problem" of the PB-PCI. Hence, we engaged in establishing a relationship between EE/N and phase retrieval performance in terms of the "forward problem" and "inverse problem" of the PB-PCI, respectively. Our results showed that, at fixed detector resolution, phase retrieval from the phase-contrast projections at the same EE/N level resulted in the consistent phase retrieval performance. Therefore, the performance of phase retrieval can be predicted based on the EE/N level and be quantitatively optimized by increasing EE/N.

Quantification of image texture in X-ray phase-contrast-enhanced projection images of in vivo mouse lungs observed at varied inflation pressures

To date, there are very limited noninvasive, regional assays of in vivo lung microstructure near the alveolar level. It has been suggested that x-ray phase-contrast enhanced imaging reveals information about the air volume of the lung; however, the image texture information in these images remains underutilized. Projection images of in vivo mouse lungs were acquired via a tabletop, propagation-based, X-ray phase-contrast imaging system. Anesthetized mice were mechanically ventilated in an upright position. Consistent with previously published studies, a distinct image texture was observed uniquely within lung regions. Lung regions were automatically identified using supervised machine learning applied to summary measures of the image texture data. It was found that an unsupervised clustering within predefined lung regions colocates with expected differences in anatomy along the cranial-caudal axis in upright mice. It was also found that specifically selected inflation pressures-here, a purposeful surrogate of distinct states of mechanical expansion-can be predicted from the lung image texture alone, that the prediction model itself varies from apex to base and that prediction is accurate regardless of overlap with nonpulmonary structures such as the ribs, mediastinum, and heart. Cross-validation analysis indicated low inter-animal variation in the image texture classifications. Together, these results suggest that the image texture observed in a single X-ray phase-contrast-enhanced projection image could be used across a range of pressure states to study regional variations in regional lung function.

Impact of a single distance phase retrieval algorithm on spatial resolution in X-ray inline phase sensitive imaging

A single-projection based phase retrieval method based on the phase attenuation duality principle (PAD) was used to compare the spatial resolution of the acquired phase sensitive and PAD processed phase retrieved images. An inline phase sensitive prototype was used to acquire the phase sensitive images. The prototype incorporates a micro-focus x-ray source and a flat panel detector with a 50 μm pixel pitch. A phantom composed of a 2 cm thick 50-50 adipose-glandular mimicking slab sandwiched with a 0.82 cm thick slanted PMMA sharp edge was used. Phase sensitive image of the phantom was acquired at 120 kV, 3.35 mAs with a 16 μm tube focal spot size under a geometric magnification (M) of 2.5. The PAD based method was applied to the acquired phase sensitive image for the retrieval of phase values. With necessary data processing, modulation transfer function (MTF) curves were determined for the estimation and comparison of the spatial resolution. The PAD processed phase retrieved values of the phantom were in good agreement with the theoretically calculated values. Phase sensitive images showed higher spatial resolution at all spatial frequencies compared to the phase retrieved images. It was noted that the high-frequency signal components in the retrieved image were suppressed that resulted in lower MTF values. When compared to the phase sensitive image, the cutoff resolution (10% MTF) for phase retrieved image dropped 32% from 15.6 lp/mm (32μm) to 10.6 lp/mm (47μm). The resolution offered by this phase sensitive prototype is radiographically enough to detect breast cancer.

Post-reconstruction 3D single-distance phase retrieval for multi-stage phase-contrast tomography with photon-counting detectors

In the case of single-distance propagation-based phase-contrast X-ray computed tomography with synchrotron radiation, the conventional reconstruction pipeline includes an independent 2D phase retrieval filtering of each acquired projection prior to the actual reconstruction. In order to compensate for the limited height of the X-ray beam or the small sensitive area of most modern X-ray photon-counting detectors, it is quite common to image large objects with a multi-stage approach, i.e. several acquisitions at different vertical positions of the sample. In this context, the conventional reconstruction pipeline may introduce artifacts at the margins of each vertical stage. This article presents a modified computational protocol where a post-reconstruction 3D volume phase retrieval is applied. By comparing the conventional 2D and the proposed 3D reconstructions of a large mastectomy specimen (9 cm in diameter and 3 cm in height), it is here shown that the 3D approach compensates for the multi-stage artifacts, it avoids refined projection stitching, and the image quality in terms of spatial resolution, contrast and contrast-to-noise ratio is preserved.

Multiscale x-ray phase-contrast tomography in a mouse model of transient focal cerebral ischemia

Cerebral ischemia is associated with a lack of oxygen and high-energy phosphates within the brain tissue, leading to irreversible cell injury. Visualizing these cellular injuries has long been a focus of experimental stroke research with application of immunohistochemistry as one of the standard approaches. It is, however, a destructive imaging technique with non-isotropic resolution, as only the two-dimensional tissue structure of a thin brain section is visualized using optical microscopy and specific stainings. Herein, we extend the structural analysis of mouse brain tissue after cerebral ischemia to the third dimension via microfocus computed tomography (µ-CT). Contrast of the weakly absorbing unstained brain tissue is enhanced by phase contrast. We show that recordings at two different magnifications and fields of view can be combined as a single approach for visualization of the associated structural alterations at isotropic resolution, from the level of the whole organ down to single cells.

Weighted-least-squares multi-filter phase imaging with partially coherent light: characteristics of annular illumination

Multi-filter phase imaging with partially coherent light (MFPI-PC) is a promising microscopic quantitative phase imaging (QPI) method that measures the phase of a transparent object. In the present work, a weighted-least-squares version is developed and applied to the important case of annular illumination. The resulting improved algorithms have largely solved the noise magnification problem associated with the original MFPI-PC in annular illumination. Simulation and microlens experiments are used to validate the new QPI method for the case of annular illumination.

Optimization of soft X-ray phase-contrast tomography using a laser wakefield accelerator

X-ray phase-contrast imaging allows for non-invasive analysis in low-absorbing materials, such as soft tissue. Its application in medical or materials science has yet to be realized on a wider scale due to the requirements on the X-ray source, demanding high flux and small source size. Laser wakefield accelerators generate betatron X-rays fulfilling these criteria and can be suitable sources for phase-contrast imaging. In this work, we present the first phase-contrast images obtained by using ionization injection-based laser wakefield acceleration, which results in a higher photon yield and smoother X-ray beam profile compared to self-injection. A peak photon yield of 1.9 × 10¹¹ ph/sr and a source size of 3 μm were estimated. Furthermore, the current laser parameters produce an X-ray spectrum mainly in the soft X-ray range, in which laser-plasma based phase-contrast imaging had yet to be studied. The phase-contrast images of a Chrysopa lacewing resolve features on the order of 4 μm. These images are further used for a tomographic reconstruction and a volume rendering, showing details on the order of tens of μm.

Monochromatic breast computed tomography with synchrotron radiation: phase-contrast and phase-retrieved image comparison and full-volume reconstruction

A program devoted to performing the first in vivo synchrotron radiation (SR) breast computed tomography (BCT) is ongoing at the Elettra facility. Using the high spatial coherence of SR, phase-contrast (PhC) imaging techniques can be used. The latest high-resolution BCT acquisitions of breast specimens, obtained with the propagation-based PhC approach, are herein presented as part of the SYRMA-3D collaboration effort toward the clinical exam. Images are acquired with a 60 - μ m   pixel dead-time-free single-photon-counting CdTe detector. The samples are imaged at 32 and 38 keV in a continuous rotating mode, delivering 5 to 20 mGy of mean glandular dose. Contrast-to-noise ratio (CNR) and spatial resolution performances are evaluated for both PhC and phase-retrieved images, showing that by applying the phase-retrieval algorithm a five-time CNR increase can be obtained with a minor loss in spatial resolution across soft tissue interfaces. It is shown that, despite having a poorer CNR, PhC images can provide a sharper visualization of microcalcifications, thus being complementary to phase-retrieved images. Furthermore, the first full-volume scan of a mastectomy sample ( 9 × 9 × 3    cm 3 ) is reported. This investigation into surgical specimens indicates that SR BCT in terms of CNR, spatial resolution, scan duration, and scan volume is feasible.

Propagation-based phase-contrast tomography of a guinea pig inner ear with cochlear implant using a model-based iterative reconstruction algorithm

Propagation-based phase-contrast computed tomography has become a valuable tool for visualization of three-dimensional biological samples, due to its high contrast between materials with similar attenuation properties. However, one of the most-widely used phase-retrieval algorithms imposes a homogeneity assumption onto the sample, which leads to artifacts for numerous applications where this assumption is violated. Prominent examples are biological samples with highly-absorbing implants. Using synchrotron radiation, we demonstrate by the example of a guinea pig inner ear with a cochlear implant electrode, how a recently developed model-based iterative algorithm for propagation-based phase-contrast computed tomography yields distinct benefits for such a task. We find that the model-based approach improves the overall image quality, removes the detrimental influence of the implant and accurately visualizes the cochlea.

Quantitative characterization and diagnosis via hard X-ray phase-contrast microtomography

Nondestructive three-dimensional (3D) micromorphological imaging technique is essential for hepatic alveolar echinococcosis (HAE) disease to determine its damage level and early diagnosis, assess relative drug therapy and optimize treatment strategies. However, the existing morphological researches of HAE mainly depend on the conventional CT, MRI, or ultrasound in hospitals, unfortunately confronting with the common limit of imaging resolution and sensitivity, especially for tiny or early HAE lesions. Now we presented a phase-retrieval-based synchrotron X-ray phase computed tomography (PR-XPCT) with striking contrast-to-noise ratio and high-density resolution to visualize the HAE nondestructive 3D structures and quantitatively segment different pathological characteristics of HAE lesions without staining process at the micrometer scale. Our experimental results of the HAE rat models at early and developed pathological stages and albendazole liposome (L-ABZ) therapeutic feeding models successfully exhibited the different HAE pathological 3D morphological and microstructural characteristics with excellent contrast and high resolution, demonstrating its availability and superiority. Moreover, we achieved the quantitative statistics and analysis of the pathological changes of HAE lesions at different stages and L-ABZ therapeutic evaluation, helpful to understanding the development and drug treatment of HAE disease. The PR-XPCT-based quantitative segmentation and characterization has a great potential in detection and analysis of soft tissue pathological changes, such as different tumors.

Phase retrieval for arbitrary Fresnel-like linear shift-invariant imaging systems suitable for tomography

We present a generalization of the non-iterative phase retrieval in X-ray phase contrast imaging applicable for an arbitrary linear shift-invariant (LSI) imaging system with a non-negligible amount of free space propagation (termed as Fresnel-like). Our novel approach poses no restrictions on the propagation distance between optical elements of the system. In turn, the requirements are only demanded for the transfer function of the optical elements, which should be approximable by second-order Taylor polynomials. Furthermore, we show that the method can be conveniently used as an initial guess for iterative phase retrieval, resulting in faster convergence. The proposed approach is tested on synthetic and experimentally measured holograms obtained using a Bragg magnifier microscope - a representative of Fresnel-like LSI imaging systems. Finally, the algorithm is applied to a whole micro-tomographic scan of a biological specimen of a tardigrade, revealing morphological details at the spatial resolution of 300 nm - limiting resolution of the actual imaging system.

Characterizing pearls structures using X-ray phase-contrast and neutron imaging: a pilot study

Some cultured and natural pearls can be reliably distinguished by visual inspection and by the use of lens and microscope. However, assessing the origin of the pearls could be not straightforward since many different production techniques can now be found in the pearl market, for example in salt or freshwater environments, with or without a rigid nucleus. This wide range of products requires the use of new effective scientific techniques. Indeed, X-ray radiography has been used by gemologists since last century as the only safe and non-destructive way to visually inspect the interior of a pearl, and recently, also X-ray computed micro-tomography was used to better visualize the inner parts of the gems. In this study we analyzed samples of natural and cultured pearls by means of two non-destructive techniques: the X-ray Phase-Contrast Imaging (PCI) and the Neutron Imaging (NI). PCI and NI results will be combined for the first time, to better visualize the pearls internal morphology, thus giving relevant indications on the pearl formation process.

Optimising complementary soft tissue synchrotron X-ray microtomography for reversibly-stained central nervous system samples

Synchrotron radiation microtomography (SRμCT) is a nominally non-destructive 3D imaging technique which can visualise the internal structures of whole soft tissues. As a multi-stage technique, the cumulative benefits of optimising sample preparation, scanning parameters and signal processing can improve SRμCT imaging efficiency, image quality, accuracy and ultimately, data utility. By evaluating different sample preparations (embedding media, tissue stains), imaging (projection number, propagation distance) and reconstruction (artefact correction, phase retrieval) parameters, a novel methodology (combining reversible iodine stain, wax embedding and inline phase contrast) was optimised for fast (~12 minutes), high-resolution (3.2-4.8 μm diameter capillaries resolved) imaging of the full diameter of a 3.5 mm length of rat spinal cord. White-grey matter macro-features and micro-features such as motoneurons and capillary-level vasculature could then be completely segmented from the imaged volume for analysis through the shallow machine learning SuRVoS Workbench. Imaged spinal cord tissue was preserved for subsequent histology, establishing a complementary SRμCT methodology that can be applied to study spinal cord pathologies or other nervous system tissues such as ganglia, nerves and brain. Further, our 'single-scan iterative downsampling' approach and side-by-side comparisons of mounting options, sample stains and phase contrast parameters should inform efficient, effective future soft tissue SRμCT experiment design.