X-ray Computed Tomography (CT) is a non-destructive imaging technique originally designed for diagnostic medicine, which was adopted for rhizosphere and soil science applications in the early 1980s. X-ray CT enables researchers to simultaneously visualise and quantify the heterogeneous soil matrix of mineral grains, organic matter, air-filled pores and water-filled pores. Additionally, X-ray CT allows visualisation of plant roots in situ without the need for traditional invasive methods such as root washing. However, one routinely unreported aspect of X-ray CT is the potential effect of X-ray dose on the soil-borne microorganisms and plants in rhizosphere investigations. Here we aimed to i) highlight the need for more consistent reporting of X-ray CT parameters for dose to sample, ii) to provide an overview of previously reported impacts of X-rays on soil microorganisms and plant roots and iii) present new data investigating the response of plant roots and microbial communities to X-ray exposure. Fewer than 5% of the 126 publications included in the literature review contained sufficient information to calculate dose and only 2.4% of the publications explicitly state an estimate of dose received by each sample. We conducted a study involving rice roots growing in soil, observing no significant difference between the numbers of root tips, root volume and total root length in scanned versus unscanned samples. In parallel, a soil microbe experiment scanning samples over a total of 24 weeks observed no significant difference between the scanned and unscanned microbial biomass values. We conclude from the literature review and our own experiments that X-ray CT does not impact plant growth or soil microbial populations when employing a low level of dose (<30 Gy). However, the call for higher throughput X-ray CT means that doses that biological samples receive are likely to increase and thus should be closely monitored.

Historically, micro-computed tomography (μCT) has been considered unsuitable for histologic analysis of unstained formalin-fixed, paraffin-embedded soft tissue biopsy specimens because of a lack of image contrast between the tissue and the paraffin. However, we recently demonstrated that μCT can successfully resolve microstructural detail in routinely prepared tissue specimens. Herein, we illustrate how μCT imaging of standard formalin-fixed, paraffin-embedded biopsy specimens can be seamlessly integrated into conventional histology workflows, enabling nondestructive three-dimensional (3D) X-ray histology, the use and benefits of which we showcase for the exemplar of human lung biopsy specimens. This technology advancement was achieved through manufacturing a first-of-kind μCT scanner for X-ray histology and developing optimized imaging protocols, which do not require any additional sample preparation. 3D X-ray histology allows for nondestructive 3D imaging of tissue microstructure, resolving structural connectivity and heterogeneity of complex tissue networks, such as the vascular network or the respiratory tract. We also demonstrate that 3D X-ray histology can yield consistent and reproducible image quality, enabling quantitative assessment of a tissue's 3D microstructures, which is inaccessible to conventional two-dimensional histology. Being nondestructive, the technique does not interfere with histology workflows, permitting subsequent tissue characterization by means of conventional light microscopy-based histology, immunohistochemistry, and immunofluorescence. 3D X-ray histology can be readily applied to a plethora of archival materials, yielding unprecedented opportunities in diagnosis and research of disease.

Although X-ray contrast agents offer specific characteristics in terms of targeting and attenuation, their accumulation in the tissue on a cellular level is usually not known and difficult to access, as it requires high resolution and sensitivity. Here, quantitative near-field ptychographic X-ray computed tomography is demonstrated to assess the location of X-ray stains at a resolution sufficient to identify intracellular structures by means of a basis material decomposition. On the example of two different X-ray stains, the nonspecific iodine potassium iodide, and eosin Y, which mostly interacts with proteins and peptides in the cell cytoplasm, the distribution of the stains within the cells in murine kidney samples is assessed and compared to unstained samples with similar structural features. Quantitative nanoscopic stain concentrations are in good agreement with dual-energy micro computed tomography measurements, the state-of-the-art modality for material-selective imaging. The presented approach can be applied to a variety of X-ray stains advancing the development of X-ray contrast agents.

We describe X-ray computed tomography (CT) datasets from three specimens recovered from Early Cretaceous lakebeds of China that illustrate the forensic interpretation of CT imagery for paleontology. Fossil vertebrates from thinly bedded sediments often shatter upon discovery and are commonly repaired as amalgamated mosaics grouted to a solid backing slab of rock or plaster. Such methods are prone to inadvertent error and willful forgery, and once required potentially destructive methods to identify mistakes in reconstruction. CT is an efficient, nondestructive alternative that can disclose many clues about how a specimen was handled and repaired. These annotated datasets illustrate the power of CT in documenting specimen integrity and are intended as a reference in applying CT more broadly to evaluating the authenticity of comparable fossils.

Changes in x-ray attenuating tissue caused by lung disorders like emphysema or fibrosis are subtle and thus only resolved by high-resolution computed tomography (CT). The structural reorganization, however, is of strong influence for lung function. Dark-field CT (DFCT), based on small-angle scattering of x-rays, reveals such structural changes even at resolutions coarser than the pulmonary network and thus provides access to their anatomical distribution. In this proof-of-concept study we present x-ray in vivo DFCTs of lungs of a healthy, an emphysematous and a fibrotic mouse. The tomographies show excellent depiction of the distribution of structural - and thus indirectly functional - changes in lung parenchyma, on single-modality slices in dark field as well as on multimodal fusion images. Therefore, we anticipate numerous applications of DFCT in diagnostic lung imaging. We introduce a scatter-based Hounsfield Unit (sHU) scale to facilitate comparability of scans. In this newly defined sHU scale, the pathophysiological changes by emphysema and fibrosis cause a shift towards lower numbers, compared to healthy lung tissue.

Walnuts are grown worldwide in temperate areas and producers are facing an increasing demand. In a climate change context, the industry also needs cultivars that provide fruits of quality. This quality includes satisfactory filling ratio, thicker shell, ease of cracking, smooth shell and round-shaped walnut, and larger nut size. These desirable traits have been analysed so far using calipers or micrometers, but it takes a lot of time and requires the destruction of the sample. A challenge to take up is to develop an accurate, fast and non-destructive method for quality-related and morphometric trait measurements of walnuts, that are used to characterize new cultivars or collections in any germplasm management process.

Laboratory x-ray micro-computed tomography (micro-CT) is a fast-growing method in scientific research applications that allows for non-destructive imaging of morphological structures. This paper provides an easily operated "how to" guide for new potential users and describes the various steps required for successful planning of research projects that involve micro-CT. Background information on micro-CT is provided, followed by relevant setup, scanning, reconstructing, and visualization methods and considerations. Throughout the guide, a Jackson's chameleon specimen, which was scanned at different settings, is used as an interactive example. The ultimate aim of this paper is make new users familiar with the concepts and applications of micro-CT in an attempt to promote its use in future scientific studies.

Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) can provide unrivalled high-resolution images of specific features and volumes of interest. However, the regions interrogated are typically very small, and sample preparation is both time-consuming and destructive. Here we consider how prior X-ray micro-computed tomography (microCT) presents an opportunity to increase the efficiency of electron microscopy in biology. We demonstrate how it can be used to; select the most promising samples and target site-specific locations; provide a wider context of the location being interrogated (multiscale correlative imaging); guide sample preparation and 3D imaging schemes; as well as quantify the effects of destructive sample preparation and staining procedures. We present a workflow utilising open source software in which microCT can be used either broadly, or precisely, to experimentally steer and inform subsequent electron microscopy studies. As automated sample registration procedures are developed to enable correlative microscopy, experimental steering by prior CT could be beneficially routinely incorporated into many experimental workflows.

Flower morphologies shape the accessibility to nectar and pollen, two major traits that determine plant-pollinator interactions and reproductive success. Melon is an economically important crop whose reproduction is completely pollinator-dependent and, as such, is a valuable model for studying crop-ecological functions. High-resolution imaging techniques, such as micro-computed tomography (micro-CT), have recently become popular for phenotyping in plant science. Here, we implemented micro-CT to study floral morphology and honey bees in the context of nectar-related traits without a sample preparation to improve the phenotyping precision and quality. We generated high-quality 3D models of melon male and female flowers and compared the geometric measures. Micro-CT allowed for a relatively easy and rapid generation of 3D volumetric data on nectar, nectary, flower, and honey bee body sizes. A comparative analysis of male and female flowers showed a strong positive correlation between the nectar gland volume and the volume of the secreted nectar. We modeled the nectar level inside the flower and reconstructed a 3D model of the accessibility by honey bees. By combining data on flower morphology, the honey bee size and nectar volume, this protocol can be used to assess the flower accessibility to pollinators in a high resolution, and can readily carry out genotypes comparative analysis to identify nectar-pollination-related traits.

Computational tomography is an important technique for developing digital agricultural models that may help farmers and breeders for increasing crop quality and yield. In the present study an attempt has been made to understand rice seed development within the panicle at different developmental stages using this technique. During the first phase of cell division the Hounsfield Unit (HU) value remained low, increased in the dry matter accumulation phase, and finally reached a maximum at the maturation stage. HU value and seed dry weight showed a linear relationship in the varieties studied. This relationship was confirmed subsequently using seven other varieties. This is therefore an easy, simple, and non-invasive technique which may help breeders to select the best varieties. In addition, it may also help farmers to optimize post-anthesis agronomic practices as well as deciding the crop harvest time for higher grain yield.

A new bismuth-based CT agent was synthesized through a facile synthesis strategy. The in vitro stability, toxicity and CT performance were evaluated. The in vivo imaging performance was investigated using three different doses (0.5, 1.2 and 5 mmol/kg) and the result obtained at 1.2 mmol/kg was compared with the clinically approved CT agent iopamidol at the same dosage.

Vertebrate models provide indispensable paradigms to study development and disease. Their analysis requires a quantitative morphometric study of the body, organs and tissues. This is often impeded by pigmentation and sample size. X-ray micro-computed tomography (micro-CT) allows high-resolution volumetric tissue analysis, largely independent of sample size and transparency to visual light. Importantly, micro-CT data are inherently quantitative. We report a complete pipeline of high-throughput 3D data acquisition and image analysis, including tissue preparation and contrast enhancement for micro-CT imaging down to cellular resolution, automated data processing and organ or tissue segmentation that is applicable to comparative 3D morphometrics of small vertebrates. Applied to medaka fish, we first create an annotated anatomical atlas of the entire body, including inner organs as a quantitative morphological description of an adult individual. This atlas serves as a reference model for comparative studies. Using isogenic medaka strains we show that comparative 3D morphometrics of individuals permits identification of quantitative strain-specific traits. Thus, our pipeline enables high resolution morphological analysis as a basis for genotype-phenotype association studies of complex genetic traits in vertebrates.

Two high resolution, 3D imaging techniques were applied to visualize and characterize sterilizing grade dual-layer filtration of liposomes, enabling membrane structure to be related with function and performance. Two polyethersulfone membranes with nominal retention ratings of 650 nm and 200 nm were used to filter liposomes of an average diameter of 143 nm and a polydispersity index of 0.1. Operating conditions including differential pressure were evaluated. X-ray computed tomography at a pixel size of 63 nm was capable of resolving the internal geometry of each membrane. The respective asymmetry and symmetry of the upstream and downstream membranes could be measured, with pore network modeling used to identify pore sizes as a function of distance through the imaged volume. Reconstructed 3D digital datasets were the basis of tortuous flow simulation through each porous structure. Confocal microscopy visualized liposome retention within each membrane using fluorescent dyes, with bacterial challenges also performed. It was found that increasing pressure drop from 0.07 MPa to 0.21 MPa resulted in differing fluorescent retention profiles in the upstream membrane. These results highlighted the capability for complementary imaging approaches to deepen understanding of liposome sterilizing grade filtration.

Unlike previous works, this open data collection consists of X-ray cone-beam (CB) computed tomography (CT) datasets specifically designed for machine learning applications and high cone-angle artefact reduction. Forty-two walnuts were scanned with a laboratory X-ray set-up to provide not only data from a single object but from a class of objects with natural variability. For each walnut, CB projections on three different source orbits were acquired to provide CB data with different cone angles as well as being able to compute artefact-free, high-quality ground truth images from the combined data that can be used for supervised learning. We provide the complete image reconstruction pipeline: raw projection data, a description of the scanning geometry, pre-processing and reconstruction scripts using open software, and the reconstructed volumes. Due to this, the dataset can not only be used for high cone-angle artefact reduction but also for algorithm development and evaluation for other tasks, such as image reconstruction from limited or sparse-angle (low-dose) scanning, super resolution, or segmentation.

A typical ground investigation for characterizing geotechnical properties of soil requires sampling soils to test in a laboratory. Laboratory X-ray computed tomography (CT) has been used to non-destructively observe soils and characterize their properties using image processing, numerical analysis, or three-dimensional (3D) printing techniques based on scanned images; however, if it becomes possible to scan the soils in the ground, it may enable the characterization without sampling them. In this study, an in-situ X-ray CT scanning system comprising a drilling machine with an integrated CT scanner was developed. A model test was conducted on gravel soil to verify if the equipment can drill and scan the soil underground. Moreover, image processing was performed on acquired 3D CT images to verify the image quality; the particle morphology (particle size and shape characteristics) was compared with the results obtained for projected particles captured in a two-dimensional (2D) manner by a digital camera. The equipment successfully drilled to a target depth of 800 mm, and the soil was scanned at depths of 700, 750, and 800 mm. Image processing results showed a reasonable agreement between the 3D and 2D particle morphology images, and confirmed the feasibility of the in-situ X-ray CT scanning system.

The structural characteristics of whole sorghum kernels are known to affect end-use quality, but traditional evaluation of this structure is two-dimensional (i.e., cross section of a kernel). Current technology offers the potential to consider three-dimensional structural characteristics of grain. X-ray computed tomography (CT) presents one such opportunity to nondestructively extract quantitative data from grain caryopses which can then be related to end-use quality.

The cranial diversity of sharks reflects disparate biomechanical adaptations to feeding. In order to be able to investigate and better understand the ecomorphology of extant shark feeding systems, we created a x-ray computed tomography (CT) library of shark cranial anatomy with three-dimensional (3D) lower jaw reconstructions. This is used to examine and quantify lower jaw disparity in extant shark species in a separate study. The library is divided in a dataset comprised of medical CT scans of 122 sharks (Selachimorpha, Chondrichthyes) representing 73 extant species, including digitized morphology of entire shark specimens. This CT dataset and additional data provided by other researchers was used to reconstruct a second dataset containing 3D models of the left lower jaw for 153 individuals representing 94 extant shark species. These datasets form an extensive anatomical record of shark skeletal anatomy, necessary for comparative morphological, biomechanical, ecological and phylogenetic studies.

X-ray computed tomography (CT) scanning is used to study the physical characteristics of soil and sediment cores, allowing scientists to analyze stratigraphy without destroying core integrity. Microbiologists often work with geologists to understand the microbial properties in such cores; however, we do not know whether CT scanning alters microbial DNA such that DNA sequencing, a common method of community characterization, changes as a result of X-ray exposure. Our objective was to determine whether CT scanning affects the estimates of the composition of microbial communities that exist in cores. Sediment cores were extracted from a salt marsh and then submitted for CT scanning. We observed a minimal effect of CT scanning on microbial community composition in the sediment cores either when the cores were examined shortly after recovery from the field or after the cores had been stored for several weeks. In contrast, properties such as sediment layer and marsh location did affect microbial community structure. While we observed that CT scanning did not alter microbial community composition as a whole, we identified a few amplicon sequence variants (13 out of 7,037) that showed differential abundance patterns between scanned and unscanned samples among paired sample sets. Our overall conclusion is that the CT-scanning conditions typically used to obtain images for geological core characterization do not significantly alter microbial community structure. We stress that minimizing core exposure to X-rays is important if cores are to be studied for biological properties. Future investigations might consider variables, such as the length and energy of radiation exposure, the volume of the core, or the degree, to which microbial communities are stressed as important factors in assessing the impact of X-rays on microbes in geological cores.

X-ray computed tomography (XCT) has become a powerful technique for studying lithium-ion batteries, allowing non-destructive 3D imaging across multiple spatial scales. Image quality is particularly important for observing the internal structure of lithium-ion batteries. During multiple rotations, the existence of cumulative errors and random errors in the rotary table leads to errors in the projection angle, affecting the imaging quality of XCT. The accuracy of the projection angle is an important factor that directly affects imaging. However, the impact of the projection angle on XCT reconstruction imaging is difficult to quantify. Therefore, the required precision of the projection angle sensor cannot be determined explicitly. In this research, we selected a common 18650 cylindrical lithium-ion battery for experiments. By setting up an XCT scanning platform and installing an angle sensor to calibrate the projection angle, we proceeded with image reconstruction after introducing various angle errors. When comparing the results, we found that projection angle errors lead to the appearance of noise and many stripe artifacts in the image. This is particularly noticeable in the form of many irregular artifacts in the image background. The overall variation and residual projection error in detection indicators can effectively reflect the trend in image quality. This research analyzed the impact of projection angle errors on imaging and improved the quality of XCT imaging by installing angle sensors on a rotary table.

An error in tomographic reconstruction parameters can result considerable artifacts in the reconstructed image, particularly in micro-computed tomography and nano-computed tomography. This study involved designing an automatic method for efficiently correcting errors resulting from incorrectly determined rotational axes and projection angles. In this method, errors are corrected by minimizing the "total variation" of a reconstructed image, and minimization is accomplished by using the gradient descent method. Compared with two previous methods, the proposed method achieved the best reconstruction results.