Principles of Different X-ray Phase-Contrast Imaging: A Review

Three-Dimensional Reconstruction-Characterization of Polymeric Membranes: A Review

Polymeric membranes serve as vital separation materials in diverse energy and environmental applications. A comprehensive understanding of three-dimensional (3D) structures of membranes is critical to performance evaluation and future design. Such quantitative 3D structural information is beyond the limit of most employed conventional two-dimentional characterization techniques such as scanning electron microscopy. In this review, we summarize eight types of 3D reconstruction-characterization techniques for membrane materials. Originated from life and materials science, these techniques have been optimized to reveal the 3D structures of membrane materials in the separation field. We systematically introduce the theories of each technique, summarize the sample preparation procedures developed for membrane materials, and demonstrate step-by-step data processing, including 3D model reconstruction and subsequent characterization. Representative case studies are introduced to show the progress of this field and how technical challenges have been overcome over the years. In the end, we share our perspectives and believe that this review can serve as a useful reference for 3D reconstruction-characterization techniques developed for membrane materials.

Radiation Detectors and Sensors in Medical Imaging

Medical imaging instrumentation design and construction is based on radiation sources and radiation detectors/sensors. This review focuses on the detectors and sensors of medical imaging systems. These systems are subdivided into various categories depending on their structure, the type of radiation they capture, how the radiation is measured, how the images are formed, and the medical goals they serve. Related to medical goals, detectors fall into two major areas: (i) anatomical imaging, which mainly concerns the techniques of diagnostic radiology, and (ii) functional-molecular imaging, which mainly concerns nuclear medicine. An important parameter in the evaluation of the detectors is the combination of the quality of the diagnostic result they offer and the burden of the patient with radiation dose. The latter has to be minimized; thus, the input signal (radiation photon flux) must be kept at low levels. For this reason, the detective quantum efficiency (DQE), expressing signal-to-noise ratio transfer through an imaging system, is of primary importance. In diagnostic radiology, image quality is better than in nuclear medicine; however, in most cases, the dose is higher. On the other hand, nuclear medicine focuses on the detection of functional findings and not on the accurate spatial determination of anatomical data. Detectors are integrated into projection or tomographic imaging systems and are based on the use of scintillators with optical sensors, photoconductors, or semiconductors. Analysis and modeling of such systems can be performed employing theoretical models developed in the framework of cascaded linear systems analysis (LCSA), as well as within the signal detection theory (SDT) and information theory.

Transport-of-intensity model for single-mask x-ray differential phase contrast imaging

X-ray phase contrast imaging holds great promise for improving the visibility of light-element materials such as soft tissues and tumors. The single-mask differential phase contrast imaging method stands out as a simple and effective approach to yield differential phase contrast. In this work, we introduce a model for a single-mask phase imaging system based on the transport-of-intensity equation. Our model provides an accessible understanding of signal and contrast formation in single-mask x-ray phase imaging, offering a clear perspective on the image formation process, for example, the origin of alternate bright and dark fringes in phase contrast intensity images. Aided by our model, we present an efficient retrieval method that yields differential phase contrast imagery in a single acquisition step. Our model gives insight into the contrast generation and its dependence on the system geometry and imaging parameters in both the initial intensity image as well as retrieved images. The model validity as well as the proposed retrieval method are demonstrated via both experimental results on a system developed in house as well as Monte Carlo simulations. In conclusion, our work not only provides a model for an intuitive visualization of image formation but also offers a method to optimize differential phase imaging setups, holding tremendous promise for advancing medical diagnostics and other applications.

Deep learning to overcome Zernike phase-contrast nanoCT artifacts for automated micro-nano porosity segmentation in bone

Bone material contains a hierarchical network of micro- and nano-cavities and channels, known as the lacuna-canalicular network (LCN), that is thought to play an important role in mechanobiology and turnover. The LCN comprises micrometer-sized lacunae, voids that house osteocytes, and submicrometer-sized canaliculi that connect bone cells. Characterization of this network in three dimensions is crucial for many bone studies. To quantify X-ray Zernike phase-contrast nanotomography data, deep learning is used to isolate and assess porosity in artifact-laden tomographies of zebrafish bones. A technical solution is proposed to overcome the halo and shade-off domains in order to reliably obtain the distribution and morphology of the LCN in the tomographic data. Convolutional neural network (CNN) models are utilized with increasing numbers of images, repeatedly validated by `error loss' and `accuracy' metrics. U-Net and Sensor3D CNN models were trained on data obtained from two different synchrotron Zernike phase-contrast transmission X-ray microscopes, the ANATOMIX beamline at SOLEIL (Paris, France) and the P05 beamline at PETRA III (Hamburg, Germany). The Sensor3D CNN model with a smaller batch size of 32 and a training data size of 70 images showed the best performance (accuracy 0.983 and error loss 0.032). The analysis procedures, validated by comparison with human-identified ground-truth images, correctly identified the voids within the bone matrix. This proposed approach may have further application to classify structures in volumetric images that contain non-linear artifacts that degrade image quality and hinder feature identification.

Tri-directional x-ray phase contrast multimodal imaging using one hexagonal mesh modulator

Objective. X-ray phase contrast imaging is a promising technique for future clinical diagnostic as it can provide enhanced contrast in soft tissues compared to traditional x-ray attenuation-contrast imaging. However, the strict requirements on the x-ray coherence and the precise alignment of optical elements limit its applications towards clinical use. To solve this problem, mesh-based x-ray phase contrast imaging method with one hexagonal mesh is proposed for easy alignment and better image visualization.Approach. The mesh produces structured illuminations and the detector captures its distortions to reconstruct the absorption, differential phase contrast (DPC) and dark-field (DF) images of the sample. In this work, we fabricated a hexagonal mesh to simultaneously retrieve DPC and DF signals in three different directions with single shot. A phase retrieval algorithm to obtain artifacts-free phase from DPC images with three different directions is put forward and false color dark-field image is also reconstructed with tri-directional images. Mesh-shifting method based on this hexagonal mesh modulator is also proposed to reconstruct images with better image quality at the expense of increased dose.Main results. In numerical simulations, the proposed hexagonal mesh outperforms the traditional square mesh in image evaluation metrics performance and false color visualization with the same radiation dose. The experimental results demonstrate its feasiblity in real imaging systems and its advantages in quantitive imaging and better visualization. The proposed hexagonal mesh is easy to fabricate and can be successfully applied to x-ray source with it spot size up to 300μm.Significance. This work opens new possibilities for quantitative x-ray non-destructive imaging and may also be instructive for research fields such as x-ray structured illumination microscopy (SIM), x-ray spectral imaging and x-ray phase contrast and dark-field computed tomography (CT).

X-ray phase-contrast microtomography of soft tissues using a compact laboratory system with two-directional sensitivity

X-ray microtomography is a nondestructive, three-dimensional inspection technique applied across a vast range of fields and disciplines, ranging from research to industrial, encompassing engineering, biology, and medical research. Phase-contrast imaging extends the domain of application of x-ray microtomography to classes of samples that exhibit weak attenuation, thus appearing with poor contrast in standard x-ray imaging. Notable examples are low-atomic-number materials, like carbon-fiber composites, soft matter, and biological soft tissues. We report on a compact and cost-effective system for x-ray phase-contrast microtomography. The system features high sensitivity to phase gradients and high resolution, requires a low-power sealed x-ray tube, a single optical element, and fits in a small footprint. It is compatible with standard x-ray detector technologies: in our experiments, we have observed that single-photon counting offered higher angular sensitivity, whereas flat panels provided a larger field of view. The system is benchmarked against known-material phantoms, and its potential for soft-tissue three-dimensional imaging is demonstrated on small-animal organs: a piglet esophagus and a rat heart. We believe that the simplicity of the setup we are proposing, combined with its robustness and sensitivity, will facilitate accessing quantitative x-ray phase-contrast microtomography as a research tool across disciplines, including tissue engineering, materials science, and nondestructive testing in general.

Deep Gauss-Newton for phase retrieval

We propose the deep Gauss-Newton (DGN) algorithm. The DGN allows one to take into account the knowledge of the forward model in a deep neural network by unrolling a Gauss-Newton optimization method. No regularization or step size needs to be chosen; they are learned through convolutional neural networks. The proposed algorithm does not require an initial reconstruction and is able to retrieve simultaneously the phase and absorption from a single-distance diffraction pattern. The DGN method was applied to both simulated and experimental data and permitted large improvements of the reconstruction error and of the resolution compared with a state-of-the-art iterative method and another neural-network-based reconstruction algorithm.

Improvement of imaging and image correction methods for the soft X-ray projection microscopy

BACKGROUND

The soft X-ray projection microscope has been developed for high resolution imaging of hydrated bio-specimens. Image blurring due to X-ray diffraction can be corrected by an iteration procedure. The correction is not efficient enough for all images, especially for low contrast chromosome images.

OBJECTIVE

The purpose of this study is to improve X-ray imaging techniques using a finer pinhole and reducing capture time, as well as to improve image correction methods. A method of specimen staining prior to the imaging was tested in order to capture images with high contrasts. The efficiency of the iteration procedure and its combined version with an image enhancement method was also assessed.

METHODS

In image correction, we used the iteration procedure and its combined version with an image enhancement technique. To capture higher contrast images, we stained chromosome specimens with the Platinum blue (Pt-blue) prior to the imaging.

RESULTS

The iteration procedure combined with image enhancement corrected the chromosome images with 329 or lower magnification effectively. Using the Pt-blue staining for the chromosome, images with high contrast have been captured and successfully corrected.

CONCLUSIONS

The image enhancement technique combining contrast enhancement and noise removal together was effective to obtain higher contrast images. As a result, the chromosome images with 329 or lower times magnification were corrected effectively. With Pt-blue staining, chromosome images with contrasts of 2.5 times higher than unstained case could be captured and corrected by the iteration procedure.

Imaging fetal anatomy

Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening is moving towards the first trimester of pregnancy. The early first trimester however remains in part, a 'black box', due to the size of the developing embryo and the limitations of contemporary scanning techniques. Therefore there is a need for images of early anatomical developmental to improve our understanding of this area. By using new imaging techniques, we can not only obtain better images to further our knowledge of early embryonic development, but clear images of embryonic and fetal development can also be used in training for e.g. sonographers and fetal surgeons, or to educate parents expecting a child with a fetal anomaly. The aim of this review is to provide an overview of the past, present and future techniques used to capture images of the developing human embryo and fetus and provide the reader newest insights in upcoming and promising imaging techniques. The reader is taken from the earliest drawings of da Vinci, along the advancements in the fields of in utero ultrasound and MR imaging techniques towards high-resolution ex utero imaging using Micro-CT and ultra-high field MRI. Finally, a future perspective is given about the use of artificial intelligence in ultrasound and new potential imaging techniques such as synchrotron radiation-based CT to increase our knowledge regarding human development.

A Review and Case Study of 3D Imaging Modalities for Female Amniote Reproductive Anatomy

Recent advances in non-invasive imaging methods have revitalised the field of comparative anatomy, and reproductive anatomy has been no exception. The reproductive systems of female amniotes present specific challenges, namely their often internal "hidden" anatomy. Quantifying female reproductive systems is crucial to recognising reproductive pathologies, monitoring menstrual cycles, and understanding copulatory mechanics. Here we conduct a review of the application of non-invasive imaging techniques to female amniote reproductive anatomy. We introduce the commonly used imaging modalities of computed tomography (CT) and magnetic resonance imaging (MRI), highlighting their advantages and limitations when applied to female reproductive tissues, and make suggestions for future advances. We also include a case study of micro CT and MRI, along with their associated staining protocols, applied to cadavers of female adult stoats (Mustela erminea). In doing so, we will progress the discussion surrounding the imaging of female reproductive anatomy, whilst also impacting the fields of sexual selection research and comparative anatomy more broadly.

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.

Exploring spectroscopic X-ray nano-imaging with Zernike phase contrast enhancement

Spectroscopic full-field transmission X-ray microscopy (TXM-XANES), which offers electrochemical imaging with a spatial resolution of tens of nanometers, is an extensively used unique technique in battery research. However, absorption-based bright-field imaging has poor detection sensitivity for nanoscale applications. Here, to improve the sensitivity, we explored spectroscopic X-ray nano imaging with Zernike phase contrast (ZPC-XANES). A pinhole-type Zernike phase plate, which was optimized for high-contrast images with minimal artifacts, was used in this study. When the absorption is weak, the Zernike phase contrast improves the signal-to-noise ratio and the contrast of images at all energies, which induces the enhancement of the absorption edge step. We estimated that the absorption of the samples should be higher than 2.2% for reliable spectroscopic nano-imaging based on XANES spectroscopy analysis of a custom-made copper wedge sample. We also determined that there is a slight absorption peak shift and sharpening in a small absorption sample due to the inflection point of the refractive index at the absorption edge. Nevertheless, in the case of sub-micron sized cathode materials, we believe that better contrast and higher resolution spectroscopic images can be obtained using ZPC-XANES.

Semi-classical Monte Carlo algorithm for the simulation of X-ray grating interferometry

Traditional simulation techniques such as wave optics methods and Monte Carlo (MC) particle transport cannot model both interference and inelastic scattering phenomena within one framework. Based on the rules of quantum mechanics to calculate probabilities, we propose a new semi-classical MC algorithm for efficient and simultaneous modeling of scattering and interference processes. The similarities to MC particle transport allow the implementation as a flexible c++ object oriented extension of EGSnrc-a well-established MC toolkit. In addition to previously proposed Huygens principle based transport through optics components, new variance reduction techniques for the transport through gratings are presented as transport options to achieve the required improvement in speed and memory costs necessary for an efficient exploration (system design-dose estimations) of the medical implementation of X-ray grating interferometry (GI), an emerging imaging technique currently subject of tremendous efforts towards clinical translation. The feasibility of simulation of interference effects is confirmed in four academic cases and an experimental table-top GI setup. Comparison with conventional MC transport show that deposited energy features of EGSnrc are conserved.

Imaging with Coherent X-rays: From the Early Synchrotron Tests to SYNAPSE

The high longitudinal and lateral coherence of synchrotron X-rays sources radically transformed radiography. Before them, the image contrast was almost only based on absorption. Coherent synchrotron sources transformed radiography into a multi-faceted tool that can extract information also from "phase" effects. Here, we report a very simple description of the new techniques, presenting them to potential new users without requiring a sophisticated background in advanced physics. We then illustrate the impact of such techniques with a number of examples. Finally, we present the international collaboration SYNAPSE (Synchrotrons for Neuroscience-an Asia-Pacific Strategic Enterprise), which targets the use of phase-contrast radiography to map one full human brain in a few years.