This PDF file contains the front matter associated with SPIE Proceedings Volume 13152, including the Title Page, Copyright information, Table of Contents, Conference Committee information, and Introduction.

The human brain contains 86 billion cells, but so far only a part could be visualized. The task corresponds to the acquisition and treatment of a petabyte-size dataset – analogous to plotting every star in the Milky Way. We demonstrated the feasibility of cellular-resolution full-brain imaging for ethanol-immersed and paraffin-embedded human brain using the tomography setup at the beamline P07 (PETRA III, DESY, Hamburg, Germany), which is operated by the Helmholtz-Zentrum Hereon. Because the beam size and the number of detector pixels limit the field-of-view to 6mm, we decided to stitch these radiographs to projections 90,000 pixels wide. The reconstructed slices allow for the detection of cells, although they contain severe artefacts. The next challenge is the optimization of the data acquisition, so that an entire brain can be made visible using typical beamtime applications. Reconstruction, artefact removal, and dissemination of such a human brain atlas is a task we are faced to. It will create a paradigm for investigating other human organs, high-performance engineering devices, and unique cultural heritage objects related to data of terabyte or even petabyte size.

Understanding the biomechanics of the human middle ear remains a challenge, primarily due to the auditory ossicles’ size, its location in the temporal bone, and subtle movements. In a recent study, dynamic synchrotron-based x-ray microtomography has been used on acoustically stimulated intact human ears, allowing the three-dimensional visualization of the ossicular chain in intact human ears for the first time. The implementation of a dedicated analysis pipeline has demonstrated the ability to resolve fast micromotions at 128Hz for two acoustic stimuli (110 and 120dB Sound Pressure Level (SPL)) on fresh-frozen human temporal bones. Measuring at lower sound pressure levels is challenging, because the ossicular vibrations become smaller, and the spatial resolution limit of the current detection system is reached. Increasing the spatial resolution without compromising the image quality or the temporal resolution would significantly extend the dynamic imaging capabilities. Here, a comparative study is conducted for a stimulation frequency of 128Hz at 120dB SPL between two synchrotron-based x-ray magnification setups: a 4x high NA macroscope (pixel size 2.75μm) versus a x10 high NA microscope (pixel size 1.1μm) in combination with the GigaFRoST fast read-out detector. It shows that an increase in resolution can indeed improve the detection of the micromovements, at the compromise of a more limited field of view.

Noise-induced hearing loss can be caused by sudden or prolonged exposure to loud noise. Noise exposure is known to contribute to the degeneration of sensory cells, disrupting the conversion of mechanical sound waves into electrical impulses and further their transmission to the brain. To determine the pathophysiological condition of the inner ear cells in animal models, the measurement of the animals' hearing is essential. The follow-up examination of the cochlea is particularly important as it provides information on the cellular morphology changes. Our aim was therefore to investigate the hair cell survival in the inner ear of mice exposed to two high noise levels using synchrotron radiation-based microtomography. Its spatial resolution allows for the reconstruction of three-dimensional images of unstained cochlea at the cellular level. We segmented the basilar membrane via automatic cell segmentation and fast manual cell removal, and determined its length using a one-dimensional Isomap embedding. After extracting its middle region and image slices aligned with it, surviving inner and outer hair cell locations were semi-automatically determined and then manually corrected using the ImageJ plugin PointPicker. These results were compared with the confocal microscopy data. The data collected provides meaningful information about healthy and damaged hair cells in the adult cochlea.

In histology, the widely used staining agents are hematoxylin and eosin (H&E), with hematoxylin marking cell nuclei and eosin staining the cytoplasm. By this, the color-coded information enables the early identification of histopathological changes using optical microscopy. However, the traditional histological process has significant drawbacks: the irreversible nature of tissue preparation often results in sample damage during dehydration, embedding, and sectioning, which can lead to the loss of crucial information. Moreover, standard microscopy techniques are limited to two-dimensional (2D) imaging, neglecting volumetric data crucial for detailed tissue analysis. X-ray imaging offers a non-destructive alternative, using contrast agents to enhance soft tissue visibility and allowing further investigations without compromising the sample. However, recently developed modified x-ray stains require adjustment for specific tissues, presenting a new challenge. Hematein can be chemically modified through the incorporation of high atomic number metals to enhance contrast in x-ray Imaging, whereas eosin staining can be augmented by increasing its concentration and acidifying the samples tissue. In this study, we aimed to demonstrate the feasibility of applying both modified hematoxylin and eosin stains to the same specimen sequentially, using a washing step with ethylenediaminetetraacetic acid (EDTA) to remove the hematein stain between scans. This novel approach preserves the distinct information provided by each stain, enabling comprehensive visualization in two separate micro-computed tomography (microCT) scans. The method was applied to biological samples from a rat strain spontaneously developing multiple endocrine tumors (MENX), provided by the Division of Neuroendocrinology at the Helmholtz Centre Munich. Specifically, the pituitary and adrenal glands of wild-type and MENX-affected rats were stained and imaged using the microCT system versaXRM-500 (ZEISS/xradia, Oberkochen Germany). The results revealed promising differentiation between healthy and affected tissues, with high-resolution imaging showing visible tumor formations, blood pools, and tissue degradation in diseased samples. This study highlights the potential of combining sequential H&E staining with microCT for enhanced tissue analysis and visualization of disease progression.

Alzheimer's disease (AD) remains one of the foremost public health challenges of our time. Recently, attention has turned to the gut-brain axis, a complex network of communication between the gastrointestinal tract and the brain, as a potential player in the pathogenesis of AD. Here we exploited x-ray Phase Contrast Tomography to provide an in-depth analysis of the link between the gut condition and AD, exploring gut anatomy and structure in murine models. We conducted a comprehensive analysis by comparing the outcomes in various mouse models of cognitive impairment, including AD, frail mice, and frontotemporal dementia affected mice. We discovered an association between substantial changes in the gut structure and the presence of amyloid-beta (Aβ) in the brain. We found that the most important gut alterations are related to Aβ occurrence in the brain. In particular, we investigated the gut morphology, the distribution of enteric micro-processes and neurons in the ileum.

Computed laminography has become a popular tool to achieve high spatial resolution in three-dimensional imaging of flat, laterally extended objects. This study explores the synergy of synchrotron full-field micro-computed and scanning x-ray fluorescence laminography imaging, along with efficient data analysis software, to enhance x-ray imaging capabilities at beamlines 2-BM and 2-ID-E of the Advanced Photon Source at Argonne National Laboratory. We discuss the advantages of laminography imaging and demonstrate examples of laminography data acquisition and reconstruction for a flat mouse bone section measured at both beamlines. Reconstructed data provided structural information from the full-field micro-computed laminography measurements and elemental distribution from the fluorescence laminography measurements. Dragonfly ORS software was used to produce high-quality interactive volume and multichannel visualizations, facilitating the analysis of the 3D reconstructed data. The proposed integration of these two modalities for efficient structural and elemental analyses of samples holds the potential for substantial advancements in imaging technology.

Edge-illumination (EI) is an established x-ray phase-contrast imaging method that relies on gratings to obtain attenuation, differential phase and dark field contrast. Current EI setups, however, have a limited geometric flexibility. That is, the gratings are designed for a fixed magnification and the period and aperture size of the sample grating determine the resolution. To enable multi-resolution EI, we propose an alternative design of the sample grating. Specifically, we introduce a grating with an adaptive period that allows multiresolution EI, and demonstrate this concept with Monte-carlo simulations of a resolution phantom at different magnifications.

Many fields, from aerospace engineering to cultural heritage, can benefit from x-ray micro computed tomography (micro-CT). However, access to x-ray imaging tools remains limited for non-expert users. The UK’s National X-Ray Computed Tomography facility (NXCT) therefore aims to provide access and expert support to academia and industry. As part of the NXCT, at UCL we have developed a unique user facility with multi-scale and multi-contrast x-ray micro-CT capabilities. Our custom system has an x-ray generator with Molybdenum and Copper targets, which can be changed to adapt the energy to the needs of an imaging experiment. The x-rays are emitted on both sides of the source allowing for two imaging stations: one at mm-sized field-of-view (FOV) with resolutions of around 1μm, the “high-resolution station”; and one at cm-sized FOV with resolutions of around 10μm, the “large FOV station”. The high-resolution station is fitted with a custom mirror which gives a monochromatic beam at 17.5keV (for Mo) and 8keV (for Cu). Both stations can be operated with phase-contrast methods such as free-space propagation or beam tracking. Access to this new imaging facility, dedicated to academic and industrial users, is supported through free-at-the-point-of-access and paid schemes.

In recent years, x-ray micro-computed tomography (micro-CT) systems with amplitude modulated beams have gained global interest. These systems feature a modulator, that is, an x-ray opaque mask with periodically spaced apertures, in front of the sample, creating an array of spatially separated beamlets. The approach offers x-ray phase contrast imaging (XPCI), which improves the contrast-to-noise ratio and reveals the presence of sub-resolution inhomogeneities by capturing, respectively, refraction and ultra-small angle scattering (dark field signal) alongside x-ray attenuation. Additionally, the modulator can increase spatial resolution, as the narrow beamlets can transfer higher spatial frequencies without requiring geometric magnification. This brief communication reviews the working principle of the approach and comments on a remaining challenge (relatively long scan times).

We explore interior tomography, a technique facilitating the observation of a region-of-interest (ROI) in computerized tomography (CT) through a strategically adjusted detector offset. By modifying the offset, we extend the field-of-view (FOV), consequently enlarging the ROI. Our innovative approach involves offsetting the detector to cover asymmetric regions during data acquisition, overcoming challenges faced by conventional reconstruction algorithms dealing with truncated projection data in interior tomography. To address these issues, we employ a deep learning (DL) network for interior tomography with a detector offset, comparing its performance with other reconstruction methods. Our DL network leverages the weighted filtered back projection (FBP) as input and incorporates the ROI map as additional information, enabling flexible ROI image acquisition within a single network. Trained on abdominal CT projection data, our network exhibits superior performance compared to existing methods. This methodology holds promise for advancing system fusion and miniaturization, particularly in omni-tomography, as it efficiently eliminates noise and artifacts in a shorter time.

Interior photon-counting computed tomography (PCCT) scans are essential for obtaining high-resolution images at minimal radiation dose by focusing only on a region of interest. However, designing a deep learning model for denoising a PCCT interior scan is rather challenging. Recently, several studies explored deep reinforcement learning (RL)-based models with far fewer parameters than those typical for supervised and self-learning models. Such an RL model can be effectively trained on a small dataset, and yet be generalizable and interpretable. In this work, we design an RL model to perform multichannel PCCT scan denoising. Because a reliable reward function is crucial for optimizing the RL model, we focus on designing a small denoising autoencoder-based reward network to learn the latent representation of full-dose simulated PCCT data and use the reconstruction error to quantify the reward. We also use domain-specific batch normalization for unsupervised domain adaptation with a limited amount of multichannel PCCT data. Our results show that the proposed model achieves excellent denoising results, with a significant potential for clinical and preclinical PCCT denoising.

In recent years, x-ray photon-counting detectors (PCDs) have become increasingly popular due to their ability to discriminate energy and low noise levels. However, technical issues (e.g., charge splitting and pulse pileup effects) can affect the data quality by distorting the energy spectrum. To address those issues, based on a deep neural network-based approach using a Wasserstein generative adversarial network (WGAN) framework for PCD data correction, we evaluate the effectiveness of pre-trained and training-from-scratch convolutional neural networks (CNNs) as perceptual loss functions to address charge splitting and pulse pileup correction challenges in photon counting computed tomography (CT) data. Different CNN architectures, including VGG11, VGG13, VGG16, VGG19, ResNet50, and Xception, are evaluated. Compared with the method using a pre-trained network, our findings indicate that training the CNNs from scratch on our dataset produces better results. It significantly affects the performance for the choice of CNN architecture as a perceptual loss in the WGAN framework. Furthermore, because recent explosive interest on transformers has suggested their potential to be useful for computer vision tasks, we also evaluate transformers to maximize the attribute-related information contained in the image feature by texture features extraction. Our study emphasizes the importance of selecting appropriate network architecture and training strategy when implementing the WGAN framework for photon counting CT data correction.

A novel method for image restoration is introduced that uses a synthetic prior intermediate (SPI) which is passed through a forward imaging operator, creating a data pair well-structured for inverse operator optimization, of which network training is of particular interest. This technique is applied to a critical problem in x-ray reconstruction: noise and artefact removal. We discuss the creation of the SPI through state-of-the-art Deep Learning Reconstruction (DLR), a spatially variant heuristic data-driven forward model for spectrally accurate noise and artefact modelling, and final image reconstruction via a convolutional neural network. Qualitative and quantitative performance is then benchmarked on a range of samples, comparing legacy reconstruction (FDK), state-of-the-art DLR, and SPI based reconstruction. SPI based reconstruction better recovers small features while also reducing residual sampling artefacts in large features. Quantitative analysis of SPI reconstruction showed a 40% throughput improvement relative to the state-of-the-art at a comparable image quality.

Here we present novel custom-made macroscope designed for high resolution, dose efficient tomographic imaging of small to medium animal models. This instrument was engineered by Optique Peter and has been recently commissioned at Biomedical Imaging and Therapy Beamlines of the Canadian Light Source. Results of the tests will be presented. In addition, we will discuss how different sCMOS cameras, which we use with the macroscope, are integrated in our data acquisition software to provide a unified control interface and to enable rapid preview of tomographic slices. This is essential when working with live animals when quick decisions need to be made during the course of the experiment.

X-ray micro/nano-tomography (multiscale CT) has been developed at SPring-8 BL47XU. The x-ray optics consists of a simple projection type imaging system for micro-tomography and a full-field x-ray microscope using a Fresnel zone plate (FZP) for nano-tomography, respectively. All components are mounted on high precision stages driven by stepper motor. It takes two or three minutes to change the mode from “micro” to “nano” or “nano” to “micro”. The spatial resolutions are 1μm and 100nm for micro and nano tomography. The width of the field of views are 800μm and 60μm. The measurement time is about 2 minutes for 1800 projections in nano-mode. The sample stages also have a possibility to switch to the setup of laminography measurement mode. The energy range is between 7keV and 15keV for multiscale CT.

This presentation introduces an x-ray scattering tensor tomography (XSTT) approach tailored to rapidly explore embedded micro-scale structures within composite materials on a centimeter scale. Thanks to advancements in rapid data acquisition and sophisticated reconstruction algorithm, this technique is extremely efficient for centimeter-scale studies of industrially significant fiber-reinforced composites (FRC). The integration of finite element method (FEM) simulations with XSTT data showcases its potential as an efficient tool for computer-aided engineering of FRCs. In addition to the time-steady characterization of FRCs, our pioneering work in tracking time-resolved deformations within viscous fluids containing micro-scale fibers also creates new opportunities for advancing rheological studies. These methodological advancements significantly impact material characterization, offering new perspectives and expanding possibilities in material science, engineering, and practical industrial applications.

X-ray phase-contrast tomography (XPCT) offers a highly sensitive 3D imaging approach to investigate different disease-relevant networks from the single cell to the whole organ. We present here a concomitant study of the evolution of tissue damage and inflammation in potential target organs of the disease in the murine model of multiple sclerosis. XPCT identifies and monitors structural and cellular alterations throughout the central nervous system, but also in the gut and eye, of mice induced to develop multiple sclerosis-like disease and sacrificed at pre-symptomatic and symptomatic time points. This approach rests on a multiscale analysis to detect early appearance of imaging indicators potentially acting as biomarkers predictive of the disease. The longitudinal data permit an original evaluation of the sequential evolution of multi-organ damage in the mouse model, shedding light on the role of the gut-brain axis in the disease initiation and progression, of relevance for the human case.

Micro-CT analysis is conventionally used to investigate mineralized tissues. However, the potential of phase-contrast and contrast-enhanced micro-CT extends to soft tissue inspection, though optimizing soft tissue contrast alongside bone remains challenging, preventing spatial inspection of bone remodeling including the cellular components. The goal was to develop a protocol for contrast-enhanced micro-CT imaging that effectively visualizes soft tissues and cells in conjunction with bone while minimizing bone attenuation by decalcification. Murine femur samples were decalcified in ethylenediaminetetraacetic acid (EDTA) and treated with three different contrast agents: i) iodine in ethanol, ii) phosphotungstic acid (PTA) in water and iii) Lugol’s iodine. Micro-CT scans were performed in the laboratory set-up SkyScan 1172 and at the SYRMEP beamline in ELETTRA. Soft- and hard-tissue contrast-to-noise ratio (CNR) and contrast efficiency after decalcification were measured. In laboratory micro-CT, iodine in ethanol and PTA provided a higher CNR for bone compared to bone marrow, while Lugol’s iodine demonstrated a three-times higher CNR in bone marrow, representing the soft tissue portion. Contrast efficiencies, measured as the percentage increase of gray value compared to its decalcified state prior to contrast enhancement, were consistent with these findings in synchrotron micro-CT. Higher resolutions and the specificity of Lugol’s iodine to cellular structures enabled detailed visualization of bone-forming cells in the epiphyseal plate. The optimized protocol for micro-CT imaging significantly enhances soft tissue visualization alongside bone, facilitating non-invasive anatomical and histological analysis. This approach shows high potential for exploring the cellular intricacies of mineralized tissues in developmental biology and pathology.

Aqueous zinc metal batteries (ZMBs) have great potential for grid energy storage applications. However, the cycle life is closely connected to the reversibility of Zn-metal plating and stripping and it is central to follow these processes in real time to advance the technology. We demonstrate how operando synchrotron X-Ray Tomographic Microscopy (XTM) can be used to visualize zinc deposition in 3D during cell operation. From the 3D renderings reveals different structures of zinc deposits and their evolution during cycling. In addition, we can quantitatively follow the volume of zinc deposits which can be directly correlated to the electrochemical data. The results of this work provide insight into real time processes in the cell and the method is applicable also to other battery chemistries.

The liquid-metal-jet microfocus source presently provides a 5 to 25µm x-ray spot with up to 1kW e-beam power. This source enables several biomedical imaging applications where high spatial resolution, high contrast and short exposure time are critical. Examples: Cellular-resolution phase-contrast imaging for virtual x-ray histology as well as for clinical resection margin assessment, potentially with rapid intraoperative feedback. Preclinical in-vivo phase-contrast small-animal lung imaging and a path towards clinical phase-contrast medical imaging. Finally, x-ray fluorescence tomography for high-resolution molecular detection of tumors in live mice.

Inline x-ray phase tomography has emerged as one of the most suitable imaging techniques for the three-dimensional examination of soft tissue at the microscopic level. Historically, this method was constrained to synchrotron radiation due to its specific requirements, such as beam coherence. However, recent advancements in detector technology (optical magnification) and x-ray sources (e.g., smaller source sizes and liquid metal sources) have enabled the transfer of this technology to laboratory settings. In this study, we investigated selected parts of an ethanol-fixated mosquito—specifically the head, abdomen, and proboscis—at the sub-cellular level using the Xradia 610 Versa (Carl Zeiss X-ray Microscopy, Inc., Dublin, California, United States) with voxel sizes as small as 180nm. A single lens of the compound eye was segmented from the data set of the head, and the focal length was calculated to be 22μm. These results demonstrate the capability of laboratory-based x-ray phase tomography for high-resolution imaging of soft tissues, facilitating detailed structural analyses previously achievable only with synchrotron radiation.

This paper presents a method for horizontally extending the field-of-view in cone-beam tomography to overcome the limitations of traditional detector sizes. The acquisition algorithms are implemented on an Exciscope Polaris phase-contrast micro-CT instrument, which ensures sufficient motion accuracy for horizontal extension solely reliant on stage positions, even at submicron voxel sizes. This innovation enables the construction of an automated data pipeline that bypasses the need for user input or image registration to recombine frames. Utilizing cloud computing for reconstruction, we efficiently handle large data sizes and computational demands. We demonstrate the method both with a reconstruction diameter of 12,500 voxels and with submicron voxel sizes, showcasing significant improvements in imaging capabilities.

A rotating-anode x-ray source and custom-built sCMOS-based detector have been integrated into a lab-based micro-CT system to demonstrate full CT acquisition in as little as 132ms. This has been used to examine the expansion of a polymer foam in 4D, with a temporal resolution of 2Hz. The system is easily adapted to carry out fast phase-sensitive multi-contrast CT with sub-10s CT acquisition times. This is made possible through the beam-tracking technique, which is capable of multi-contrast CT using only a single shot per projection angle, while also being compatible with incoherent sources. This paves the way to dynamic, phase-sensitive, multi-contrast micro-CT in the laboratory.

High-resolution synchrotron x-ray computed tomography (CT) in situ pull-out tests with stepwise increased loading were performed to investigate the force transfer between a shape memory alloy (SMA) wire and the surrounding epoxy polymer matrix. The advancing interfacial failure was observed. The stochastic surface structure of the SMA wire was utilized to determine the axial and radial strains introduced into the SMA wire during the test by performing digital volume correlation on the reconstructed surface data. The global and local strain of the embedded SMA wire volume could be correlated with the force of the first interfacial failure. Using image segmentation on the cross-sections derived from the reconstructed CT volume data, the growth of the delamination along the observed length of the embedded SMA wire for increasing load levels was measured. In addition, the advancing interfacial failure was correlated with changes in the cross-sectional area of the SMA wire due to transverse contraction. The local surface strain characteristics of an embedded SMA wire during CT of an in situ pull-out test were compared to a non-embedded SMA wire loaded in situ. It was found that the polymer matrix exerts an external stress on the SMA wire, constraining its radial strain. Thereby, the study reveals that interfacial failure is not only a shear-stress-induced failure, but shear strain and even more normal strain due to transverse contraction of the SMA wire plays an important role too.

Printed circuit boards (PCBs) are indispensable components that enable the functionality of modern electronics applications. Ranging from various densities and uniqueness by design, the attack surfaces of these devices are vast and complex. In secure/critical domains like medical, automotive, and defense, the authenticity of these devices is critical to mitigate losses in trust and security. Not only does their complexity and responsibility in a hardware system pose an issue, but the globalization of their supply chain further emphasizes the necessity of methods to validate their designs. In this paper, the authors propose a novel framework for furthering PCB trust by addressing pitfalls in verifying the connectivity design of PCBs. Incorporating data from both imaging modalities into a cohesive model framework aims to address the shortfalls of single-modality autonomous netlist approaches.

The Non-Clinical Tomography Users Research Network (NoCTURN) is working to advance Findability, Accessibility, Interoperability, and Reuse (FAIR) and Open Science (OS) practices in the domain of tomographic imaging. By leveraging input from a broad community of tomography educators, researchers, and industry stakeholders, NoCTURN is engaging the international scientific tomographic community to stimulate improvements for tomographic imaging standards that focus on FAIR and OS principles. We aim to reduce the barriers to entry that isolate individuals and research labs, and we anticipate that developing community standards and improving methodological reporting will enable long-term, systemic changes necessary to aid those at all levels of experience in furthering their access to and use of tomographic imaging.

Shark vertebral bodies (centra) possess remarkable resistance to millions of cycles of large in vivo strains exceeding 4 to 8%. These strains are enormous for a mineralized tissue, and it appears that the centra evolved to achieve this performance through a hierarchy of structures spanning dimensions from centimeters to nanometers. At the 1μm scale, blocks cut from centra and imaged with synchrotron microCT demonstrate that the centra tissue consists of closely spaced, mineralized trabeculae. An outstanding question is: How do these trabeculae deform to accommodate these large strains. This paper presents recently obtained synchrotron microCT results on in situ loading of blocks of shark centra and examines the deformation modes of the interconnected array of trabeculae.

X-ray computed laminographic tomography (CLT) is a viable tool for creating high-throughput volumetric imaging of large, planar samples. In this work, we present a self-supervised deep image restoration workflow to produce noise-free, artifact-free volumetric reconstructions for laminographic tomography. We demonstrate our CLT method on a variety of samples scanned with an in-house prototype system, showing that our proposed method notably outperforms classic reconstruction methods, that has the potential for more accurate detection of defects and estimation of critical dimensions, thereby providing a feasible solution for rapid inline inspection and failure analysis in advanced integrated circuits packaging.

A critical challenge in modern x-ray imaging is achieving high-resolution for large volumes. Countless material applications demand statistically relevant samplings of defects, encompassing secondary phases, inclusions, phase segregation, cracks, pores, and more. There is an inherent tradeoff between the volume that can be imaged and the resolution of the image. Imaging a large volume may yield a statistically relevant sample size but at low resolution, rendering it inadequate for detecting the smallest defects. Conversely, high spatial resolution imaging captures intricate details over a small volume, raising questions about statistical relevance. This paper demonstrates the application of a commercial deep-learning-based x-ray tomography reconstruction method for solid state battery analysis. By harnessing the power of two distinct datasets—a high-volume scan and a high-resolution scan —a deep neural network is trained on correspondences between low and high-resolution images. Following training, the model performs reconstruction of the large-volume dataset at high-resolution. The model is demonstrated for defect detection in a commercial solid state battery. A 3mm² battery sample is imaged at a 3-micron pixel resolution. A second interior tomography is captured at 1.5-micron pixel resolution. The DL model reconstructs the battery volume at 1.5-micron resolution, revealing defects and particle inclusions previously concealed by low-resolution, large-volume scans. Reconstruction is validated using direct comparisons between the deep-learning-based XCT reconstruction and traditional high-resolution imaging. A femtosecond laser was employed to cut the sample, exposing these defects for imaging with scanning electron microscopy (SEM). Multiple defects and microstructural features revealed in the deep-learning-based reconstructions were confirmed during this validation process.

Congenital defects in dental enamel are diverse in pathology and etiology, and designing treatment tools for the clinic requires fundamental research on the process of enamel formation. Rodent incisors are the model of choice, and microcomputed tomography (μCT) is often the first method of comparison between models. Quantitative comparison of μCT data requires segmentation of mineralized tissues in the jaw; previously, we demonstrated the ability of convolutional neural networks to quickly and accurately segment mineral gradients in mouse jaws in synchrotron μCT images. Here we greatly expand on that work and present a protocol for adapting base networks to new pathologies and data types. With collaborators, we have amassed a collection (~80 TB) of μCT images from laboratory machines and synchrotrons representing 18 genetic mouse lines. We demonstrate the ability of adapted networks to segment these new data without compromising accuracy. Specifically, our networks adapted well to data collected with different x-ray sources, voxel dimensions, and phenotypes. In fully segmented data, we demonstrate the ability to visualize stages during enamel formation and compare rates of change in mineral density during the process. Importantly, our work has revealed insights about how and when mineral deposition goes awry in defective enamel. We envision widespread use of these tools. Once base networks are deployed to a repository for artificial neural networks, researchers will be able to use the protocol we present here for using modest amounts of their data to adapt a network to their own analysis.

gVirtualXray (gVXR) is an open-source framework that relies on the Beer-Lambert law to simulate x-ray images in real time on a graphics processor unit (GPU) using triangular meshes. A wide range of programming languages is supported (C/C++, Python, R, Ruby, Tcl, C#, Java, and GNU Octave). Simulations generated with gVXR have been benchmarked with clinically realistic phantoms (i.e. complex structures and materials) using Monte Carlo (MC) simulations, real radiographs and real digitally reconstructed radiographs (DRRs), and x-ray computed tomography (CT). It has been used in a wide range of applications, including real-time medical simulators, proposing a new densitometric radiographic modality in clinical imaging, studying noise removal techniques in fluoroscopy, teaching particle physics and x-ray imaging to undergraduate students in engineering, and XCT to masters students, predicting image quality and artifacts in material science, etc. gVXR has also been used to produce a high number of realistic simulated images in optimization problems and to train machine learning algorithms. This paper presents applications of gVXR related to XCT.

Phase-contrast computed tomography enables the visualization of weakly-absorbing samples with high contrast. Speckle-based imaging (SBI) is a phase-sensitive X-ray imaging technique that requires the use of a wavefront marker (typically a sandpaper) to retrieve multi-modal information: absorption, refraction and scattering. These quantities are derived by analyzing the distortions in a reference pattern generated when the sample is inserted into the beam. The Unified Modulated Pattern Analysis (UMPA) model is a speckle-tracking method capable of processing such datasets. While high-resolution tomographic reconstructions can be achieved at the synchrotron, there is usually a trade-off with sample dimensions. Here, we use UMPA with a multi-frame approach for signal retrieval, enabling the expansion of the reconstructed field-of-view (FOV) by moving the sample instead of the modulator transversely to the beam. We demonstrate this technique on a human placental tissue sample.

A static, multi-source x-ray Computed Tomography (CT) system facilitates rapid multi-view x-ray radiography, significantly improving the efficiency of cargo scanning. However, reconstructing images from sparse-view x-ray data in cargo scanning is challenging, particularly when conventional deep learning reconstruction techniques are hampered by a scarcity of training data. This work proposes the application of Deep Image Prior (DIP), which does not require training data, to reduce undersampling reconstruction artifacts arising from sparse-view and restricted opening angle acquisition in x-ray CT systems tailored for large-scale cargo scanning in harbors. The work particularly targets a rectangular multi-source x-ray CT system, featuring up to 40 equidistantly distributed static x-ray sources with a 30-degree opening angle. Our study demonstrates that DIP improves the quality of of sparse-view cargo CT in terms of PSNR and SSIM compared to traditional reconstruction methods.

The Helmholtz-Zentrum Hereon is operating imaging beamlines for X-ray tomography (P05 IBL, P07 HEMS) for academic and industrial users at the synchrotron-radiation source PETRA III at DESY in Hamburg, Germany. The high flux density and coherence of synchrotron radiation enable high-resolution in situ/operando/in vivo tomography experiments and phase-contrast imaging techniques, respectively. Large amounts of 3D and 4D data are collected that are difficult to process and analyze. Recently, we have explored machine learning approaches for the reconstruction, processing and analysis of synchrotron-radiation tomography data. Here, we report on the application of supervised learning for multimodal data analysis to generate a virtual 3D histology, digital volume correlation of 4D in situ tomography data, and instance segmentation. Furthermore, we present findings related to unsupervised learning in the context of semantic segmentation.

The Helmholtz-Zentrum Hereon, Germany, is operating the user experiments for microtomography at the beamlines P05 and P07 using synchrotron radiation produced in the storage ring PETRA III at DESY, Hamburg, Germany. Attenuation-contrast and phase-contrast techniques were established to provide an imaging tool for applications in biology, medical science and materials science. In the recent years we rebuilt the data preprocessing pipeline before reconstruction to provide different scanning techniques to investigate samples larger than the field of view of the x-ray beam. Within this paper the hardware requirements and calibration used at the imaging stations will be given. Furthermore, we adjust the preprocessing pipeline to deal with different mechanical accuracies of the translation / rotation stages used for addressing the full volume of the sample. Several examples using low photon energies at P05 and high photon energies at P07 will demonstrate the new stitching pipeline.

The acquisition of large tomography volumes, exceeding the typical detector field-of-view, requires advanced acquisition techniques. Current approaches are the tiling of local reconstructed volumes or the tiling in projection space, also known as mosaic tomography. Reconstruction tiling has the advantage that standard reconstruction software can be used and acquisition can be interrupted and resumed relatively easily. The disadvantage is that there is the need for volume registration and transformation. Projection tiling is faster and more dose efficient, however a custom reconstruction pipeline is required, registration in projection space is challenging due to lower contrast, and there is a high sensitivity to mechanical instabilities. In this work we propose a third, hybrid approach, to profit from the advantages of projection tiling, but limit the risks. The volume to be imaged is covered by overlapping cylinders, each corresponding to the reconstructed volume of one mosaic tomogram. The number of rings per cylinder and the total number of cylinders can be tuned to the specimen at hand. We demonstrate this approach for a 2cm-wide section of a human brain stem, imaged at the Anatomix beamline of Synchrotron Soleil, France with 0.65µm voxel size, resulting in reconstructed slices 29,650 voxels wide. For mosaic reconstruction we used our team’s existing pipeline. For stitching of volumes, image registration was performed in the overlap regions. As pairwise displacements between cylinders are not independent, we modified the registration approach to force a consistent solution. The results of the hybrid acquisition in seven tiles with four rings were compared to a pure projection tiling approach with eight rings and to local regions representing reconstruction tiling. In conclusion, we propose an extended field of view acquisition scheme building on the speed and dose efficiency of mosaic acquisition, but relaxing the requirements for mechanical and beam stability.

Reconstructing x-ray CT data on cubic voxels leads to discretization errors due to the finite size of these voxels. These errors are known as Partial Volume Effects (PVE). Reconstructing x-ray data on a tetrahedral mesh adapted to the sample generates a memory efficient multi-resolution representation that has the potential to diminish PVE. Such an adaptive method requires reconstructing attenuation values of the scanned sample on tetrahedra of the mesh. While a wide variety of open source software is available for iterative reconstruction methods on cubic voxels, research on fast iterative reconstructions on tetrahedral meshes is limited. In this work, we present an extension of the GPU accelerated CAD-ASTRA mesh projector that solves the inverse problem on tetrahedra. With an appropriate starting condition, such a representation has the potential to greatly increase the accuracy of a CT reconstruction.

With the advent of new detector technologies, on-the-fly 3D data reconstruction became an important requirement at synchrotron-based micro-tomography beamlines to follow dynamics processes inside the samples. FaXToR beamline of the Spanish synchrotron ALBA will provide a high data throughput, making use of state-of-the-art CMOS fast detectors. Therefore, particular care is required in order to cope with the computing needs. The IT infrastructure will accomplish 3D data reconstruction, distributed processing and PB-sized data storage. Herein, the infrastructure and data workflow implemented at FaXToR are described, reaching a data throughput of 7.5GB/s and an on-the-fly 3D data reconstruction and visualization of more than three volumes per second.

Transport of immune cells, nutrients and waste products via the cerebrospinal fluid (CSF) has been implicated in the development of neurological disorders. Using time-resolved in vivo microtomography, we investigated pulsatile motion of CSF spaces in the mouse brain as a potential driver of CSF flow. Here we present a method for detecting motion captured in murine brain images acquired in vivo at the European Synchrotron Radiation Facility. Anesthetized mice were placed in a heated holder that was designed to minimize head motion and maintain physiological body temperature. Contrast agent was infused into the ventricle to improve visibility of the CSF spaces. Projections were retrospectively sorted based on the ECG recording. Cardiac phase images were reconstructed in 10ms intervals from the ECG peak and automatically analyzed for decorrelation. Motion was automatically quantified by non-rigid registration. Regions with high intensity structures, large motion magnitudes, large improvements in image similarity due to registration, or at the contrast-enhanced ventricles were visually inspected for structures with motion artifacts prior to registration. We detected mainly motion in the nasopharynx, skin, ear channels, and bones in the range of 2.3 to 14.8µm magnitude. Small motion artifacts were detectable only for high-contrast structures. No misalignments were visible for the contrast-enhanced ventricles at a voxel resolution of 6.30 to 6.45µm. In the future, dedicated active gating to ensure regular sampling and local scans with improved spatial resolution will be used to investigate the limits to the detection of in vivo ventricular motion in mice.

This study explores recent developments in quantitative phase-contrast microtomography using Talbot Array Illuminators (TAI) combined with Unified Modulated Pattern Analysis (UMPA). We first compare the performance of the TAI-based method for phase-retrieval with propagation-based imaging (PBI) for analyzing a Mg-10Gd bone implant sample that violates the single-material assumption. Our results demonstrate that the TAI method yields a significantly higher contrast-to-noise ratio (CNR) compared to PBI (101.68 vs. 54.37, an 87% improvement) while maintaining comparable edge sharpness. The TAI method also visualizes a substructure of the degradation layer, which appears comparatively blurred in the PBI images. Additionally, we introduce a hanging-rotation-axis approach for imaging paraffin-embedded samples in an ethanol bath, aiming to reduce edge enhancement artifacts caused by large electron density differences. Preliminary results indicate that the TAI-based images of a paraffin-embedded lymph node show improved uniformity in background intensity, though some additional low-frequency noise is observed. All experiments were conducted at the High Energy Materials Beamline (HEMS), PETRA III, DESY, operated by Hereon. Our findings highlight the potential of TAI-based phase-contrast imaging for complex, multi-material samples and suggest avenues for further optimization of the technique.

Achieving cellular-resolution imaging of intact human organs is critical for improving our understanding of anatomy and pathology. Traditional clinical imaging and histological methods often fail to provide both global and detailed views of entire organs. Hierarchical Phase-Contrast Tomography (HiP-CT), an approach leveraging the ESRF’s Extremely Brilliant Source upgrade to perform non-destructive, high-resolution imaging of intact human organs addresses these limitations. HiP-CT allows for whole organ scans at <20μm/voxel, with localized zooms down to 2μm/voxel, bridging the gap between clinical imaging and histology. This multi-scale capability enables detailed examination of anatomical structures and pathologies. We provide here the last developments of HiP-CT, along with various applications on human organs. HiP-CT has shown potential in research areas such as COVID-19 affected lungs and cardiac studies. Despite challenges like high radiation doses and data management, HiP-CT represents a significant advancement in biomedical imaging, with future research aiming to extend its application, correlative imaging upscale and downscale, and enhance data accessibility.

The Advanced Photon Source Upgrade (APS-U) project is set to revolutionize hard x-ray research. The upgraded machine will provide increase coherent flux and brightness in x-ray beams by a factor of 500. Many x-ray techniques will significantly benefit from this enhancement, particularly in terms of speed and achievable resolution. The Imaging Group at APS operates three specialized beamlines—2-BM, 7-BM, and 32-ID—focused on full-field imaging and ultra-high-speed applications. These beamlines cover up to three orders of magnitude in both spatial and temporal resolution. As part of the APS-U, the Imaging Group will further improve its capabilities, especially in terms of speed and image quality. These advancements will enable new possibilities for researchers conducting multi-scale, multi-modal, and time-resolved experiments. A significant addition to the group will be the future installation of a Projection Microscope at 32-ID, which will bridge the resolution gap between nano-tomography, currently achieved with the Transmission X-ray Microscope at 32-ID, and micro-tomography at 2-BM and 7-BM.

Imaging the oxygenation distribution at a high spatial resolution in deep tissues such as bone marrow is important because it helps us in understanding the oxygenation’s role on stem cell proliferation and differentiation inside the bone marrow. Current technologies have limitations in imaging the oxygenation of deep targets. To overcome these limitations, x-ray Luminescence Computed Tomography (XLCT) has the potentials to image the oxygenation of bone marrow at a spatial resolution close to the focused x-ray beam size, which is better than 150 micrometers. In this study, oxygenation sensing films have been developed. Then, we have improved our XLCT imaging system by adding optical filters for measurements of photons at multiple wavelengths so that we are able to image the oxygenation of deep film targets. Then, we have conducted a phantom experiment to validate this approach. We obtained the oxygen concentration images by measuring the ratios of the XLCT images at two wavelengths.

This study evaluates the impact of charge summing correction (CSC) on a Cadmium Telluride (CdTe) Photon Counting Detector in breast CT. A laboratory benchtop system that consists of a 0.1mm pixel pitch CdTe detector and a tungsten anode x-ray source. Images were acquired at 55kVp with 2mm Al external filtration under three different tube currents: 25, 100, and 200mA. Performance was assessed using contrast to noise ratio (CNR), modulation transfer function (MTF), noise power spectrum (NPS), and iodine quantification. Anticoincidence (AC) and single pixel (SP) modes were compared, both with signal-to-thickness calibration and FDK reconstruction. AC mode showed enhanced low-energy contrast and accurate iodine quantification, while SP mode had better CNR at low-energy. High x-ray fluence reduced AC mode uniformity, but not SP. Results suggest that CSC in breast CT improves iodine quantification but at the cost of increased noise in low-energy images. These effects are dependent on the studied system and operational parameters.

This paper introduces and discusses the development of an interesting multimodal CT imaging technique, called full x-ray particle information CT (PI-CT), which combines x-ray transmission, fluorescence, and scattering tomography using a polychromatic x-ray source. The PI-CT allows for the simultaneous reconstruction of high-resolution tissue structure images, quantitative imaging of high-Z element concentrations, and electron density distributions. During x-ray photons passing through an object, photoelectric effects and Compton scattering may occur, resulting in x-ray attenuation and the generation of scattering and fluorescent photons. All these interaction information is innovatively utilized in PI-CT to detect and image different physical quantities inside the object. X-ray transmission CT could image the object’s high-resolution structure. X-ray fluorescence CT could realize the quantitative imaging of high-Z agents. Compton scattering CT could reconstruct the electron density information, which may have better contrast in weak absorption radiation imaging cases, such as lung imaging. Therefore, with the help of functional imaging nanoparticles, PI-CT can provide both high-resolution tissue structure images and highly sensitive molecular functional images of living animals, which provides a new multimodal tool for tumor diagnosis and treatment. Experimental results demonstrate the potential of PI-CT in enhancing multimodal CT imaging, particularly in tumor diagnosis and treatment applications.

Biological soft tissues are functional agglomerates of cells. They constitute the microenvironment where intercellular communication occurs. In turn, their woven structure underlies mechanical properties that contribute to their roles in the context of the organs and the organisms that contain them. Therefore, determining the density and spatial distribution of cells within the tissue offers key information for understanding its physiological properties and its state. X-ray holographic nanotomography is a non-destructive imaging technique capable of resolving subcellular details in biological tissues that has shown promising advantages to study the structure of neuronal circuits. However, the dimensions of the datasets required – covering volume landscapes of ~mm³ – make manual annotation of individual nuclei an unrealistic task. We developed and trained an automated image segmentation classifier that accurately detects and segments cell nuclei in mouse brain tissue imaged with x-ray holographic nanotomography, and that generalises to similar datasets obtained from biological replicates with minimal additional ground truth. It provides the spatial locations and morphologies of the ~80k nuclei per dataset with a high recall. It harnesses the strengths of a high-performance computing cluster and embeds the curated results in two main simplified outcomes: a data table and explorable image segmentations and meshes associated with the original dataset, in a browser-compatible format that simplifies proofreading by multiple users. The classifier we present here can be readily integrated into an automated analytical pipeline for histological datasets obtained with synchrotron x-ray holographic nanotomography in the context of systems neuroscience as well as broader tissue life science studies.

We report about the experimental work related to hierarchical structures at the Diamond I13L beamlines. The I13-2 Imaging and I13-1 Coherence beamlines provide imaging with micro- and nano-resolution. The Diamond II upgrade for the synchrotron source and the OCTOPI upgrade for I13L provide new opportunities for expanding the existing scientific areas in multiscale and operando imaging. We describe the scientific research benefitting from the instrumental upgrade. Comparable recording times across all length scales will enable hierarchical operando imaging. With the implementation of automated high-throughput data acquisition and analysis, large numbers of samples will be analyzed.

Imaging natural history collections is becoming an important conservation tool that also serves research purposes. Herbaria are at the forefront of this new area, where automatic conveyor belts can scan thousands of sheets per day. The production of high quality images is used as a tool for inventory, monitoring, communication, data exchange between scientists and new taxonomic identifications. Microtomography of collection items with these aims is much more time-consuming and expensive. While it has been so far limited to rare and important specimens such as types or reference specimens (i.e., historically or scientifically important specimens; the data generated takes conservation to another level. This is because nit captures not only surface features, but also very fine texture and internal structures are digitally recorded, depicting the object in almost all its complexity and dimensions. Generating this kind of data helps researchers achieve their goals, provides first-hand scientific data, limits further handling of sometimes fragile specimens and, can help reduce the ecological footprint of scientific travel. In this work, we illustrate the power of microtomography in conservation work by imaging fossil type specimens (i.e. remains of extinct organisms used to designate new species) which are witnesses of past life on our planet. They provide information on how today’s biodiversity has evolved and are a good indicator for the past climates. In addition, they often fascinate a wide audience and are therefore good ambassadors for communicating scientific findings. Recording them with the help of x-ray microtomography should therefore be a general goal, which we illustrate here with examples.

The publications on x-ray imaging with a focus on micro- and nanotomography are becoming more and more interdisciplinary and combine the developments in instrumentation and algorithms with dedicated applications. The current challenges relate to synchrotron radiation sources of the fourth generation, to the establishment of phase contrast in laboratory-based systems, to the sound integration of machine learning into data analysis, to the dissemination of the big data, to the suitable preparation of the objects for tomographic imaging, and to the closer and closer collaboration between the experts, for example to address clinical needs for improving human health. This paper summarizes selected key aspects of the more than 60 contributions in the 15th volume on Developments in X-ray Tomography.

Born in 1928, the German physicist Ulrich Bonse had a challenging time as pupil during and after World War II. He had to serve as Luftwaffenhelfer (anti-aircraft auxiliary). Starting in 1949, he studied physics at the University of Münster, Germany. Under the supervision of Eugen Kappler, Ulrich Bonse developed an x-ray-based method to experimentally determine strain fields of defects in silicon and germanium single crystalline materials - a timely research topic closely related to the invention of the transistor. His awarded PhD-thesis was internationally recognised. Thus, he was invited to US in 1961 and became guest professor at Cornell from 1963 to 1965, where he developed together Michael Hard the first x-ray interferometer, a development awarded by the German Physical Society. So it is no surprise that in 1970 Ulrich Bonse became Professor in Physics and the Founding Director of x-ray and neutron imaging research on the Angstrom scale at the University of Dortmund, Germany.

Ulrich Bonse became a prominent figure in the world of x-ray characterization in the 1960s and continued to be active into the 2000s. Other papers in the volume will cover Bonse’s work in interferometry and in phase contrast tomography, and this account will be limited to x-ray tomography with absorption contrast. The author first encountered Bonse at a NATO Advanced Study Institute where Bonse lectured on x-ray sources and where the author was a beginning PhD student. In 1979, synchrotron x-radiation was quite novel for materials and other applications, so Bonse’s lecture was very important in setting the stage for future developments. Now, the author routinely has beamtime a dozen or more times a year, something which he could not have imaged in 1979. Throughout his career, Bonse was a strong advocate for the storage ring community, and the second section of this account discusses the timeline of storage rings becoming available for experimenters. The third section of this paper describes the early development of microComputed Tomography (microCT), a field where Bonse made important contributions. The fourth section summarizes “Developments in X-ray Tomography I-V of SPIE, the conference that Bonse founded.

Ulrich Bonse left a great mark on the development of x-ray CT technology. Here, his another great achievement in x-ray optics is highlighted, which is known as “Bonse-Hart x-ray interferometer” developed in collaboration with Michael Hart. These two contributions by him are closely related to my research; I reported the first phase-contrast x-ray computed tomography by combining Bonse-Hart interferometry and tomography. The Bonse-Hart interferometer had already been realized in 1965 thanks to its monolithic structure that allowed stability in the angstrom-scale region. This invention opened up various opportunities in the experiments with hard x-rays and even neutrons. Phase-contrast x-ray computed tomography is one of them. In memory of Ulrich Bonse, an overview of the interferometer is given, and the early stage of the development of phase-contrast x-ray computed tomography and its current status are described.

The development of full-field imaging at synchrotron radiation sources in Europe was driven by the scientific research of Ulrich Bonse together with many students from the Department of Experimental Physics I at the University of Dortmund, Germany. Using bending magnets at the storage ring DORIS III at DESY, the first full-field tomograms were conducted in parasitic mode. With the dedicated operation of DORIS for synchrotron radiation user experiments and the integration of a bypass to DORIS to integrate wiggler insertion devices the development of attenuation- and phase-contrast SRμCT as a research tool for 3D investigation of biological and materials science samples became possible. Within this paper the experimental developments form hardware to software for running full-field imaging from DORIS via ESRF to PETRA III based on the work of Ulrich Bonse will be elucidated.

Ulrich Bonse's contributions to x-ray imaging have shaped the field, particularly through his pioneering work on x-ray interferometry, attenuation-based and phase-contrast-based micro-CT, as well as his service to the SPIE community. This paper honors his legacy by exploring the connection between his foundational work and recent AI advancement. Specifically, we will discuss how generative AI can enhance x-ray interferometric imaging and clinical micro-CT. Finally, we will make remarks on the SPIE CT Conference series he created and its international impact.

Multimodal imaging has shown great potential in cancer research by concurrently providing anatomical, functional, and molecular information in live, intact animals. During preclinical imaging of small animals like mice, anesthesia is required to prevent movement and improve image quality. However, their high surface area-to-body weight ratio predisposes mice, particularly nude mice, to hypothermia under anesthesia. To address this, we developed a detachable mouse scanning table with heating function for hybrid x-ray and optical imaging modalities, without introducing metal artifacts. Specifically, we employed Polylactic Acid (PLA) 3D printing technology to fabricate a customized scanning table, compatible with both CT and optical imaging systems. This innovation enables seamless transportation of the table between different imaging setups, while its detachable design facilitates maintaining a clutter-free operational environment within the imaging systems. This is crucial for accommodating various projects within the same scanner. The table features positioned fixation points to secure mice, ensuring positional consistency across imaging modalities. Additionally, we integrated a carbon nanotube-based heating pad into the table to regulate the body temperature of mice during examinations, providing an ethical and effective temperature maintenance solution. Our evaluations confirmed the table’s ability to maintain a 30g water bag at approximately 40℃, effectively regulating mouse body temperature to an optimal 36℃ during preclinical imaging sessions. This scanning table serves as a useful tool in preclinical cancer research, offering a versatile tool that upholds animal welfare standards.

This research explores the use of x-ray induced acoustic computed tomography (XACT) in vascular imaging to assess parameters like oxygen content, blood flow, and velocity. XACT’s high-resolution imaging capabilities could revolutionize diagnostics and monitoring of vascular conditions by enabling non-invasive, real-time evaluations. The study will investigate the feasibility of obtaining quantitative measurements of blood oxygenation, along with flow rates and velocities, using XACT, potentially enhancing our understanding of vascular physiology and improving clinical outcomes.

We study the bimodal imaging of neutron and x-ray simultaneous tomography in complementary ways and feasibility test for HANARO thermal neutron facility. This approach combines the advantages of x-rays, which exhibit low penetration for high atomic numbers, with neutrons that have high cross-sections for light elements such as Li, Be, and B. This combination allows for a comprehensive understanding of the internal structure of materials, extending the exploration range beyond what is possible with conventional x-ray and neutron technologies. We additionally demonstrate the correction of scattering in neutron images using black body techniques, which successfully enhances visibility and effectively reduces scattering-induced noise. Furthermore, we discuss the potential for quantitative and qualitative comparative evaluations by applying an unrolling method as a new approach to straighten bent or twisted objects. The results suggest the future applicability of neutron and x-ray simultaneous tomography at HANARO and indicate the potential for integration with quantitative techniques such as energy-selective imaging and interferometry.

When using neutron scattering information in a conventional grating interferometer, there were significant limitations due to the configuration of the interferometer system in obtaining a graph of the autocorrelation length that confirms the internal structure of the object. To solve this problem, a simulation was conducted to obtain the autocorrelation length over a wide range by changing the system configuration using a single absorption grating (inverse pattern simulation). Using spatial harmonic imaging techniques for ancient Korean coins, we obtained images of various modalities and revealed the differences between genuine and counterfeit coins. This experiment was conducted at PSI's BOA.

Edge Illumination (EI) X-ray phase contrast imaging (XPCI) is a promising technique that, next to conventional attenuation contrast, provides phase contrast and dark field contrast. Opposed to conventional x-ray imaging though, EI-XPCI is more vulnerable to focal spot drifts, leading to intensity changes in the acquired projections. As a result, attenuation, phase, and dark field contrast parameters that are estimated from these projections also suffer from these variations. In this work, through accurate phase contrast simulations using the recently developed CAD-ASTRA toolbox, we study the effect of the focal spot drifts on EI-XPCI parameter estimation. These variations are then modeled by computing eigen flat fields (EFFs). Subsequently, the EFFs are used to normalize the projections corresponding to each phase step of an EI-XPCI acquisition. Results indicate that dynamic flat field correction (FFC) based on EFFs outperforms conventional FFC in EI-XPCI.

The Talbot-Lau grating interferometer advances x-ray imaging by enabling phase contrast, dark-field imaging, and differential phase contrast imaging with lab-based x-ray sources, alongside conventional absorption images. This study explores directional dark-field imaging (DDFI) to reveal microstructural details in samples. Using a Talbot-Lau setup, we measured materials like carbon fiber, demonstrating DDFI's effectiveness in visualizing anisotropy, orientation, and microstructure. By rotating the sample and analyzing scattering directions, we showcase DDFI's ability to describe complex material features. Our findings indicate DDFI's potential in materials science, offering new insights into sample characterization and analysis.

A multiscale computed tomography (CT) system consisting of three CT systems with different field of view (FOV) and spatial resolutions, has been developed at BL20XU of SPring-8. One is a micro-CT (FOV 1mm/pixel size 0.5μm) with a simple projection optics from the undulator source. The second is a wide-field CT (FOV 6mm/pixel size 3μm), in which a beam diffuser is inserted in the optical path to widen the beam irradiation area to the sample. The third is a nano-CT for high resolution (FOV 60μm, pixel size 30 to 40nm), which is based on a full-field x-ray microscope using a Fresnel zone plate as the x-ray objective. This means that these three systems cover scales of more than five orders of magnitude in real space. These measurement modes can be easily changed between each other by users in 1 min without removing the sample from the stage. In order to measure samples with several millimeters in size, the nano-CT is capable of high energy regions of 15 to 37.78keV. In addition, a working distance of approximately 100mm is provided around the sample, allowing measurement with various test equipment, facilitating in-situ observation and operando measurement.

At SPring-8 BL28B2, Hoshino et al. developed a CT measurement technique using high-energy x-rays (200keV) to observe internal structures of materials. Combining this with a sample exchange robot, high-def x-ray camera, and SP8-DC computer tech, they automated the process from measurement to image reconstruction. The system captures projection images with a maximum field of view of 48mm x 1.2mm, handling larger specimens by repeated scans and stacking CT images. Measuring a sample with the size of 48mm x 10mm takes about 1.5 hours with the effective pixel size of 3.72um/pixel. Then, transferring the data to SP8-DC is completed within half an hour, and image reconstruction takes approximately 6 hours.

The combined application of x-ray diffraction contrast tomography and micro-computed tomography provides valuable and comprehensive insights, allowing for an in-depth understanding of phase composition and microstructure of materials. In this paper, we outline the current state of this methodology at the EH4 station of the P07 beamline, operated by Hereon, and present two practical applications within the field of metallic biomaterials for the development of new implant materials, inspiring further research and innovation in this area. Using magnesium alloys as implant materials offers several advantages, because they hold potential for temporary implants that naturally degrade within the body. These implants gradually dissolve over time, thereby promoting bone healing. Research in this area not only requires an understanding of the structural and phase changes in magnesium implants but also necessitates an investigation of the surrounding bone tissue structure. Although magnesium implant materials and bone tissue belong to different material classes, the combination of x-ray diffraction contrast tomography and micro-computed tomography enables detailed analysis of their microstructure and phase composition. As a result, we can extract information on porosity, phase composition, and crystal parameters around hybrid magnesium-titanium implants and obtain detailed information on the ultrastructure of bone tissue in a non-destructive manner.

Nano Computed Tomography (nanoCT) is a powerful tool for non-destructive three-dimensional specimen visualization and investigation at the submicron scale. Here, we present our lensless lab-based nanoCT setup, which combines a nanofocus x-ray source with a photon-counting detector. On the one hand, the x-ray source’s coherence enables propagation-based phase-contrast, which is beneficial for investigating low-absorbing specimens, e.g., in virtual 3D-histology of biopsies and material science. We describe the setup, discuss its optimization, focusing on acquisition speed and field of view increase, and present the latest results.

X-ray fluorescence computed tomography (XFCT) is an emerging imaging modality that enables quantification of the distribution of high-Z elements, including gold, gadolinium, and iodine, in diverse biomedical applications, by specifically detecting the x-ray fluorescence (XRF) emitted from the target element. Pixelated semiconductor detectors such as Cadmium Telluride (CdTe) and Cadmium Zinc Telluride (CZT) sensors are particularly suited for XFCT imaging due to their high energy and spatial resolution capabilities. However, their performance degrades because of multi-pixel events, which occur when an incident photon deposits energy across multiple adjacent pixels. In this study, we implement corrections for the energy loss during charge sharing. Furthermore, for bi-pixel events occurring within the gadolinium K α energy and caused by the escape and re-capture of detector elements’ x-ray fluorescence, we correct the interaction location. To validate the efficacy of the charge sharing energy loss correction and fluorescence escape events location correction, we utilized a PMMA phantom filled with Gadolinium saline solutions at concentrations ranging from 0 to 1.2mg/ml for XFCT imaging. The implemented corrections enhanced the contrast noise ratio in the gadolinium region. These improvements in XFCT imaging quality are useful for the preclinical investigation of precise tumor diagnosis and treatment using high atomic number element nanoparticles, and for other semiconductor detector-based imaging modalities.

This study presents an innovative approach to constructing a representative system matrix in x-ray imaging forward models. The approach leverages the combination of machine learning algorithms and fundamental physical principles through the use of physics-informed machine learning (PIML). The main goal is to seamlessly integrate machine learning algorithms with core physical principles to provide a nuanced perspective on the development of an interpretable and adaptive system matrix. In contrast to traditional data-intensive methods, this research intentionally prioritizes the incorporation of physics-based constraints into the machine learning framework. The methodology involves carefully extracting relevant features from x-ray imaging data to capture essential object characteristics, which are then integrated into a machine learning model. By including physics-based constraints, the model aligns with the underlying principles that govern x-ray interactions. Through rigorous mathematical validation and preliminary experimentation, the approach demonstrates its feasibility, particularly in situations where acquiring extensive datasets is challenging. From a technical standpoint, the strength of this methodology lies in the inherent adaptability and interpretability of the system matrix, which are crucial for accurate image reconstruction and measurement prediction. The implications of this research span diverse domains and highlight the potential transformative effects on x-ray imaging applications in electronics, medical imaging, and material inspection. In the realm of electronics, the adaptable system matrix improves non-destructive testing by aiding in defect detection and ensuring the reliability of electronic components. In medical imaging, enhanced interpretability leads to improved diagnostic accuracy while reducing radiation exposure. In material inspection, this approach facilitates the identification of structural anomalies and material composition, thereby advancing quality control practices. While recognizing the preliminary nature of the framework, this study lays the groundwork for future research at the intersection of machine learning and physics in x-ray imaging, representing a progressive step towards unlocking transformative possibilities for enhanced accuracy and adaptability across various domains.

Continuous acquisition is a scanning technique in which the object rotates without interruption while the x-ray projections are acquired. This results in a considerable reduction in scanning time, compared to a step-and-shoot acquisition. While a reduced scanning time is preferred, motion during acquisition leads to motion artifacts in the reconstructed image. Existing techniques that reduce these motion blurring artefacts assume a purely rotational motion with a constant angular velocity. We propose a technique with a generalized motion model that allows for a flexible incorporation of object motion. While it is also possible to model acceleration, this remained unvalidated. Based on simulated data, we demonstrate the applicability of this technique for scans in which the object rotationally accelerates.

In our correlative characterisation studies of biodegradable and permanent metal bone implants, we have performed both synchrotron-radiation microtomography (SR-μCT) and histology on the same samples. Histological staining is still the gold standard for tissue visualisation yet requires multiple time-consuming sample preparation steps (fixing, embedding, sectioning and staining) before imaging is performed on individual slices, in contrast to the non-invasive and 3D nature of tomography. In the process of correlating the corresponding data sets, we are able to combine advantages of both modalities by using machine learning methods to generate artificially stained 3D virtual histology datasets from SR-μCT datasets. For this we have developed an automated registration tool to find and fit the correct virtual tomographic plane to each histology slice. Preliminary results are promising after training a modified cycle generative adversarial network on our data, with two different histological stainings.

Imaging anatomical features of the human brain at cellular resolution currently relies on series of physical sections with related slicing artefacts. So far, microtomography has been employed to image an entire human brain at a voxel size of 20µm and selected regions using 6µm. This study aims to demonstrate the feasibility of imaging the entire human brain with cellular resolution without the need for physical sectioning using hard x-ray computed tomography. 1.2mm high sections of two human brains, one embedded in ethanol, the other in paraffin, were imaged using microtomography at the P07 beamline at DESY, Hamburg, Germany with a monochromatic beam at 67keV. The extended field of view necessary to cover the ca. 10 cm wide specimens at 2.54µm voxel size was realized by projection tiling with eight to ten rings. The resulting reconstructed slices measured 39,000×39,000 voxels. This synchrotron radiation-based study shows the feasibility of employing x-ray tomography to image the entire human brain with isotropic voxels of 2.54µm resolution. Next, we need to tackle the vertical stitching of several 10,000 slices of 6GB each, posing the challenge of processing the big data of an entire PB-sized human brain and making it accessible to the research community.

The human eye’s cornea is vital for visual clarity and quality of life. Besides proteoglycans, an adequate hydration contributes to a transparent cornea by uniform distribution of collagen fibrils. Understanding the cell distribution within the multi-layered cornea is fundamental to investigate corneal physiology and pathology. Micro-CT imaging potentially enables a spatial examination of the cornea. This study employs contrast-enhanced micro-CT to demonstrate the feasibility and expectable precision of X-ray imaging of the intricate multi-layered human cornea. Human donor corneas were hydrated to different degrees, mimicking the in-vivo state of edema formation. Tissue samples were then immersed in Lugol’s iodine for contrast enhancement and scanned by the laboratory micro-CT Skyscan 2211. The effects in the soft tissue contrast were evaluated accordingly. The contrast-to-noise ratios (CNR) for the cell layers, specifically the epithelium and endothelium, were 8.67 ± 1.17 and 5.84 ± 0.53, respectively. In comparison, the stromal tissue exhibited a significantly lower CNR of 1.81 ± 0.29. This discrepancy highlights Lugol's iodine's strong affinity for binding cells, which enhanced the contrast of individual stromal cells relative to the surrounding collagen fibrils, and the potential to be visualized with contrast-enhanced micro-CT. The present study underscores the potential of contrast-enhanced micro-CT for soft tissue applications with multi-laminar ultrastructure. This advanced imaging technique might enhance our understanding of corneal biology and its applications in clinical settings. Additionally, the specific binding properties of Lugol’s iodine demonstrated may extend to other biological samples and thus opens new pathways for virtual/3D histology.

Synchrotron-radiation phase-contrast tomography is a non-invasive technique that allows high-resolution imaging of soft structures. We present the first results of the cochlea (inner ear) of a harbor porpoise (Phocoena phocoena). Samples were analyzed at a high spatial resolution using synchrotron-radiation propagation-based phase-contrast microtomography at the high-energy materials science beamline (HEMS) P07, operated by Hereon, at the storage ring PETRA III at DESY. Since these samples are larger than the x-ray beam profile, a scanning and projection-based stitching approach was employed. Stitching of the acquired raw data sets resulted in centimeter-sized reconstructions with 2.54μm voxel size and volumes ranging from 280GB to 5.2TB. Synchrotron-radiation phase-contrast tomography proved to be a suitable technique to image the spiral ganglion cells and other structures of the inner ear of a harbor porpoise.

Single photon emission computed tomography (SPECT) is commonly used with radioiodine scintigraphy to evaluate patients with multiple diseases such as thyroid cancer. The clinical gamma camera for SPECT contains a mechanical collimator that greatly compromises dose efficiency and limits diagnostic performance. The Compton camera is emerging as a promising alternative for mapping the distribution of radio-pharmaceuticals in the thyroid, since the Compton camera does not require mechanical collimation and in principle does not reject gamma ray photons. In this study, a high-efficiency tomographic imaging system is designed with a Compton camera for thyroid cancer imaging. A Timepix3-based Compton camera is selected for collecting gamma photons emitted from an I-131 phantom, and the backprojection filtration algorithm is applied for image reconstruction. The results demonstrate the feasibility of the Compton camera for high efficiency SPECT imaging and also the limitations that need further efforts to address.

This study scrutinizes the limitations and challenges of applying non-destructive techniques such as Scanning Acoustic Microscopy (SAM) and 3D x-ray imaging for testing 3D and 2.5D integrated circuit (IC) packaging configurations. As the semiconductor industry moves towards advanced packaging technologies like 2.5D and 3D heterogeneous integration, which integrates various dies or chiplet components vertically and horizontally to enhance device performance and reduce costs, ensuring the reliability of these complex structures becomes paramount. This paper presents a comprehensive review of the current state-of-the-art non-destructive methods used for physical inspection, characterization, and failure analysis, with a focus on SAM and 3D x-ray imaging. It discusses the pressing challenges faced by these methods due to ongoing miniaturization and the need for high precision in inspecting densely packed components. An empirical investigation is conducted through a case study of a multi-die advanced packaging scenario to evaluate the practical utility of SAM and 3D x-ray techniques. This examination includes comparisons of resolution, analysis window size, aiming to understand the benefits of integrating these imaging modalities. The study also explores the future needs and opportunities for advancement in imaging hardware and algorithm development for automated signal interpretation and AI-assisted defect detection. This investigation highlights the critical role of non-destructive methods in advancing semiconductor packaging technologies while addressing their current limitations and the path forward for enhancing IC package integrity and reliability.

The semiconductor industry’s advancements in advanced packaging and heterogeneous integration have outpaced traditional failure analysis and quality assurance capabilities. Existing non-destructive characterization methods face challenges regarding the small-scale interconnections and multi-layer stack structure of HI packaging. This paper explores the challenges in assuring the reliability of these heterogeneously integrated ICs and proposes a multi-modal approach combining Scanning Acoustic Microscopy and X-ray imaging for comprehensive analysis. SAM offers high-resolution acoustic imaging but faces difficulties in characterizing small-scale interconnects. Similarly, x-ray imaging provides advantageous resolution, but struggles with large sample sizes and long acquisition times. By combining these modalities, this research aims to bolster failure analysis and quality assurance for these up-and-coming technologies.

Palatoplasty in infants with cleft palate aims to reconstruct the intricate three-dimensional anatomy and restore the velopharyngeal function, which is essential for swallowing, speech, and ventilation of the middle ear through the opening of the Eustachian tube. The non-destructive analysis of the microarchitecture around the pterygoid hamulus using hard x-rays should enhance the existing knowledge from dissection and histological studies. Specifically, the micro-anatomical relationship between the palatine aponeurosis, the tendon of the tensor veli palatini muscle, and the pterygoid hamulus must be characterized to understand their structural relationship and functional implications. At the cellular level, the arrangement of fibers within muscle fascicles needs to be clarified. The right half of a historical plastinated infant cadaveric head was examined with two laboratory-based micro computed tomography (μCT) systems: phoenix|xray nanotom^® m for imaging of the entire specimen with a pixel size of 55μm; and Zeiss Xradia 610 Versa for local tomography with a pixel size of 3.4μm. Using synchrotron radiation-based microtomography, additional measurements were performed with a pixel size of 3.24μm. The resulting images were rigidly registered and analyzed. Automated threshold-based segmentation of bones and manual segmentation of muscles, tendons, and aponeurosis, were performed to visualize their topographic relationships in three dimensions. An unstained segment of a human gracilis muscle was examined using the Exciscope Polaris with a pixel size of 0.35μm, and the fiber architecture was visually inspected. Laboratory-based x-ray μCT systems are suitable for virtual-histology examination of soft tissues and visualization of subcellular structures therein. Synchrotron radiation-based μCT with phase retrieval provided additional contrast within the plastinated soft tissues. The findings of this study support the hypothesis that the palatal muscles form a complex muscle sling around the pterygoid hamulus, underscoring the importance of preserving this bony protuberance during cleft palate repair.