arXiv subjects

Kaye S. Morgan

Publications and source records attributed to Kaye S. Morgan.

At least 19 recordsLinked to original sources

arXiv2026

X-ray dark-field imaging from intensity flow: A Fokker-Planck approach to grating interferometry

Grating interferometry is a promising diagnostic technique that enables simultaneous acquisition of three complementary, synergistic X-ray images: transmission, differential phase, and dark-field. Its key advantage over other setups is its ability to use large pixels and, hence, large-area detectors, as well as its compatibility with low-coherence, compact X-ray sources, both of which are key factors for human-scale imaging. It has already demonstrated strong potential for chest imaging applications, including the diagnosis of pulmonary emphysema, fibrosis, and cancer. To retrieve transmission, differential phase, and dark-field images from data, an algorithm is required to separate the distinct mechanisms contributing to measured contrast. Since its realization, this image-retrieval step has remained fundamentally unchanged. In this work, we develop a novel transmission- and dark-field retrieval algorithm for grating-interferometry derived from the X-ray Fokker-Planck equation. To demonstrate and validate our Fokker-Planck algorithm, we apply it to experimental measurements of a test sample and to data from a mouse chest acquired with varying exposure times and added Poisson noise. The retrieved images were qualitatively and quantitatively compared with those retrieved using a conventional sinusoidal-fitting approach. Across both samples, the Fokker--Planck method produced images consistent with conventional retrieval, with a comparable signal-to-noise ratio. Notably, our Fokker-Planck method suppresses artefacts arising in the conventional approach under grating perturbations (e.g., structural defects like scratches) and reduced flux or visibility, yielding smoother and more reproducible images. Additionally, we demonstrate that our Fokker-Planck method has an advantage over the conventional dark-field retrieval method for fast sample imaging with short exposure times and high noise.

physics.med-ph↗

arXiv2026

Neighbor2Inverse: Self-Supervised Denoising for Low-Dose Region-of-Interest Phase Contrast CT

Propagation-based X-ray phase-contrast imaging (PBI) enables high-contrast visualization of lung structures and holds strong medical potential. However, safe translation to the clinic will require a substantial radiation dose reduction, which inevitably increases image noise. Supervised convolutional-neural-network-based denoising can restore image quality but depends on paired low- and high-dose datasets, which are rarely available in practice. Self-supervised methods avoid this limitation, yet most are not well adapted to the inverse problem of PBI computed tomography (CT). We introduce Neighbor2Inverse, a self-supervised denoising framework designed for low-dose PBI-CT that generalizes to clinical CT. Building on the Neighbor2Neighbor principle, each noisy projection is subsampled into two variants that preserve structural information but contain independent noise realizations. These are reconstructed separately, and the resulting pairs are used to train a denoising network directly in the image domain. We benchmark the proposed method against established analytical and self-supervised denoising approaches. In region-of-interest PBI CT experiments, Neighbor2Inverse achieves superior noise suppression while preserving fine structural details, as demonstrated by improved contrast-to-noise ratio, spatial resolution, and composite image quality metrics. Competitive performance is also observed on clinical CT data under simulated low-dose conditions. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. Code, data, and interactive figures are available at https://github.com/J-3TO/Neighbor2Inverse.

cs.CV↗

arXiv2026

Paraxial diffusion-field retrieval. II. Fokker-Planck generalization of the transport-of-intensity equation

The transport-of-intensity equation (TIE), namely the continuity equation associated with a coherent paraxial optical wavefield, is widely used for phase retrieval. It is a second-order partial differential equation which may be solved for the phase of a coherent paraxial field such as a monochromatic scalar optical beam, given the intensity and longitudinal intensity derivative in a plane perpendicular to the optical axis. We show how the coherent flow associated with the TIE may be augmented by a diffusive flow associated with a scalar or tensor diffusion field. Such diffusive flow can arise via scattering from unresolved spatially random microstructure in an illuminated sample, blurring effects of an extended chaotic source that illuminates the sample, the resolution-reducing effect of shot noise in detected intensity images of the sample, and the sharpening effect (negative diffusion) associated with scattering from sharp sample edges. Augmenting the TIE's modeling of coherent flow with a diffuse-flow channel leads to a Fokker-Planck extension to this equation. Two different augmentations are obtained, using several complementary derivations. The inverse problems of phase retrieval and diffusion-field retrieval are then considered, for defocus-based imaging and mask-based imaging. When symmetric overfocus and underfocus images are used for phase retrieval, the diffusive term drops out and our Fokker-Planck formalism implies that any ensuing TIE-based phase-retrieval method needs no modification in light of our formalism. However, the same focal-series dataset---typically an infocus image, a weakly overfocused image, and a weakly underfocused image---may also be employed to access the additional channel of information associated with the Fokker-Planck diffusion field. Our formalism is applicable to visible light, x-ray, electron, and neutron imaging.

physics.optics↗

arXiv2025

Quantitative Stain Mapping in X-ray Virtual Histology

Virtual histology is an emerging field in biomedicine that enables three-dimensional tissue visualization using X-ray micro-computed tomography. However, the method still lacks the specificity of conventional histology, in which parts of the tissue are selectively highlighted using targeted stains. Though some first X-ray stains have been developed to address this issue, their precise location and quantity inside the tissue volume remain largely unknown. In this work, we present a novel approach to virtual histology that simultaneously captures electron number density and X-ray attenuation values through modulation-based X-ray imaging with a structured phase modulator. These complementary measurements enable decomposition of tissue volumes into basis materials, which allows the extraction of three-dimensional maps of molar contrast agent distribution alongside morphological details on the micrometer scale -- here demonstrated on murine kidneys. The concentration values are validated against the established method of K-edge subtraction imaging. We also create a direct bridge from X-ray to visible light imaging by detecting the same stain both using classical histology and our proposed X-ray approach. Our methodology opens new possibilities for biomedical research into disease progression by providing quantitative three-dimensional stain mapping across entire tissue volumes alongside high-contrast morphology, enabling deeper insights into disease mechanisms.

physics.med-ph↗

arXiv2025

Demonstrating a family of X-ray dark-field retrieval approaches on a common set of samples

Sensitive to scattering from unresolved sample structures, the dark-field channel in full-field X-ray imaging provides complementary information to that offered by conventional attenuation and phase-contrast methods. A range of experimental dark-field techniques and retrieval algorithms have been recently developed to extract this signal by directly resolving dark-field-associated local image blurring with a high-resolution camera. While the underlying physical mechanism that generates dark-field contrast is generally defined similarly across the methods, no comparison of these dark-field techniques using identical samples has been conducted. In this paper, dark-field imaging data from two samples were acquired using three emerging dark-field setups at a synchrotron: propagation-based, single-grid, and speckle-based X-ray imaging. Dark-field images were then reconstructed using a variety of retrieval algorithms--some requiring only a single sample exposure, others multiple; some performing local, pixel-wise analysis, and others operating globally on entire images. We find that the dominant contribution to dark-field contrast--arising from diffuse scattering from unresolved microstructures or multiple refractions through larger, potentially resolved structures--is consistently recovered across all approaches, demonstrating mutual agreement. However, some differences emerge for structures that are spatially varying. We attribute these differences to the idea that each technique has a different internal ruler, a sensitivity scale for dark-field retrieval influenced by both the experimental design and algorithmic assumptions of the technique. This study is intended to guide dark-field imaging users in selecting the most appropriate technique for their imaging goals and to motivate future research into dark-field sensitivity and sources of dark-field contrast across different methods.

physics.optics↗

arXiv2025

High-energy X-ray phase-contrast CT of an adult human chest phantom

Propagation-based phase-contrast X-ray imaging is a promising technique for in~vivo medical imaging, offering lower radiation doses than traditional attenuation-based imaging. Previous studies have focused on X-ray energies below 50 keV for small-animal imaging and mammography. Here, we investigate the feasibility of high-energy propagation-based computed tomography for human adult-scale lung imaging at the Australian Synchrotron's Imaging and Medical Beamline. This facility is uniquely positioned for human lung imaging, offering a large field of view, high X-ray energies, and supporting clinical infrastructure. We imaged an anthropomorphic chest phantom (LungMan) between 50 keV and 80 keV across the range of possible sample-to-detector distances, with a photon-counting and an integrating detector. Strong phase-contrast fringes were observed with the photon-counting detector, even at high X-ray energies and a large pixel size relative to previous work, whereas the integrating detector with lower spatial resolution showed no clear phase effects. Measured X-ray phase-shifting properties of LungMan aligned well with reference soft tissue values, validating the phantom for phase-contrast studies. Imaging quality assessments suggest an optimal configuration at approximately 70 keV and the longest available propagation distance of 7.5 m, indicating potential benefit in positioning the patient in an upstream hutch. This study represents the first step towards clinical adult lung imaging at the Australian Synchrotron.

physics.med-ph↗

arXiv2025

Estimations of lung structural properties from a single propagation-based dark-field X-ray image

In this investigation, we applied a single-projection dark-field imaging technique to gain statistical information on the smallest airway structures within the lung$\unicode{x2014}$the alveoli$\unicode{x2014}$focusing on their size and number as key indicators of lung health. The algorithm employed here retrieves the projected thickness of the sample from a propagation-based phase contrast image using the transport-of-intensity equation. The first Born approximation is then used to isolate the dark-field signal associated with edge scattering, which increases the visibility of microstructure boundaries. PMMA spheres of known sizes were imaged first as an idealised alveolar model. The dark-field signal was then recovered from propagation-based phase-contrast X-ray images of the lungs of small mammals using this method. The retrieved dark-field signal was found to be proportional to both the alveolar size ($R^2 = 0.85$) and the number in projection ($R^2 = 0.69$), and these measurements could be combined to provide an estimate of the total surface area of the alveolar interfaces ($R^2 = 0.78$). This demonstrates the approach's ability to indicate lung health using the dark-field signal retrieved from a single-phase-contrast X-ray image.

physics.med-ph↗

arXiv2024

Single-exposure X-ray dark-field imaging via a dual-energy propagation-based setup

X-ray dark-field imaging visualises scattering from sample microstructure, and has found application in medical and security contexts. While most X-ray dark-field imaging techniques rely on masks, gratings, or crystals, recent work on the Fokker--Planck model of diffusive imaging has enabled dark-field imaging in the propagation-based geometry. Images captured at multiple propagation distances or X-ray energies can be used to reconstruct dark-field from propagation-based images but have previously required multiple exposures. Here, we show single-exposure dark-field imaging by exploiting the harmonic content in a monochromatised synchrotron beam and utilising an energy-discriminating photon-counting detector to capture dual-energy propagation-based images. The method is validated by filming time-varying samples, showing the advantage of the dark-field contrast in analysing dynamic evolution. We measure and adjust for the impact of detector charge-sharing on the images. This work opens the way for low-dose and dynamic dark-field X-ray imaging without the need for a high-stability set-up and precision optics.

physics.optics↗

arXiv2024

In vivo 4D x-ray dark-field lung imaging in mice

X-ray dark-field imaging is well-suited to visualizing the health of the lungs because the alveoli create a strong dark-field signal. However, time-resolved and tomographic (i.e., 4D) dark-field imaging is challenging, since most x-ray dark-field techniques require multiple sample exposures, captured while scanning the position of crystals or gratings. Here, we present the first in vivo 4D x-ray dark-field lung imaging in mice. This was achieved by synchronizing the data acquisition process of a single-exposure grid-based imaging approach with the breath cycle. The short data acquisition time per dark-field projection made this approach feasible for 4D x-ray dark-field imaging by minimizing the motion-blurring effect, the total time required and the radiation dose imposed on the sample. Images were captured from a control mouse and from mouse models of muco-obstructive disease and lung cancer, where a change in the size of the alveoli was expected. This work demonstrates that the 4D dark-field signal provides complementary information that is inaccessible from conventional attenuation-based CT images, in particular, how the size of the alveoli from different parts of the lungs changes throughout a breath cycle, with examples shown across the different models. By quantifying the dark-field signal and relating it to other physical properties of the alveoli, this technique could be used to perform functional lung imaging that allows the assessment of both global and regional lung conditions where the size or expansion of the alveoli is affected.

physics.med-ph↗

arXiv2024

Separating edges from microstructure in X-ray dark-field imaging: Evolving and devolving perspectives via the X-ray Fokker-Planck equation

A key contribution to X-ray dark-field (XDF) is X-ray diffusion by sample structures smaller than the imaging system's spatial resolution. However, some XDF techniques report that resolvable sample edges also generate XDF. Speckle-based X-ray imaging (SBXI) extracts XDF by analyzing sample-imposed changes to a reference speckle pattern's visibility. We present an algorithm for SBXI (a variant of our Multimodal Intrinsic Speckle-Tracking (MIST) algorithm) capable of separating these two distinct XDF contrast mechanisms. The algorithm uses the 'devolving' X-ray Imaging Fokker-Planck equation as its forward model and then solves the associated multimodal inverse problem, to retrieve sample attenuation, phase, and XDF. Previous MIST variants were based on the evolving Fokker-Planck equation, which considers how a reference-speckle image is modified by introducing a sample. The devolving perspective instead considers how the image collected in the presence of the sample and speckle membrane optically flows in reverse, to generate the reference-speckle image when the sample is removed from the system. We compare single- and multiple-exposure multimodal retrieval algorithms from the two Fokker-Planck perspectives. We demonstrate that the devolving perspective can distinguish between two physically different XDF contrast mechanisms; unresolved microstructure- and sharp-edge-induced XDF. This was verified by applying the retrieval algorithms to two experimental data sets. We anticipate that this work will be useful in: Yielding a pair of complementary XDF images that separate sharp-edge diffuse scatter from unresolved microstructure diffuse scatter. XDF computed tomography, where the strong edge XDF can lead to tainting streaking artefacts. Sample preparation, as samples will not need to be embedded since the strong XDF edge signal seen between the sample and air can be separated out.

physics.optics↗

arXiv2024

Correcting directional dark-field x-ray imaging artefacts using position-dependent image deblurring and attenuation removal

In recent years, a novel x-ray imaging modality has emerged that reveals unresolved sample microstructure via a "dark-field image", which provides complementary information to conventional "bright-field" images, such as attenuation and phase-contrast modalities. This x-ray dark-field signal is produced by unresolved microstructures scattering the x-ray beam resulting in localised image blur. Dark-field retrieval techniques extract this blur to reconstruct a dark-field image. Unfortunately, the presence of non-dark-field blur such as source-size blur or the detector point-spread-function can affect the dark-field retrieval as they also blur the experimental image. In addition, dark-field images can be degraded by the artefacts induced by large intensity gradients from attenuation and propagation-based phase contrast, particularly around sample edges. By measuring any non-dark-field blurring across the image plane and removing it from experimental images, as well as removing attenuation and propagation-based phase contrast, we show that a directional dark-field image can be retrieved with fewer artefacts and more consistent quantitative measures. We present the details of these corrections and provide "before and after" directional dark-field images of samples imaged at a synchrotron source. This paper utilises single-grid directional dark-field imaging, but these corrections have the potential to be broadly applied to other x-ray imaging techniques.

physics.med-ph↗

arXiv2023

X-ray dark-field via spectral propagation-based imaging

Dark-field X-ray imaging is a novel modality which visualises scattering from unresolved microstructure. Most dark-field imaging techniques rely on crystals or structured illumination, but recent work has shown that dark-field effects are observable in straightforward propagation-based imaging (PBI). Based on the single-material X-ray Fokker--Planck equation with an a priori dark-field energy dependence, we propose an algorithm to extract phase and dark-field effects from dual-energy PBI images. We successfully apply the dark-field retrieval algorithm to simulated and experimental dual-energy data, and show that by accounting for dark-field effects, projected thickness reconstruction is improved compared to the classic Paganin algorithm. With the emergence of spectral detectors, the method could enable single-exposure dark-field imaging of dynamic and living samples.

physics.med-ph↗

arXiv2023

Paraxial diffusion-field retrieval

Unresolved spatially-random microstructure, in an illuminated sample, can lead to position-dependent blur when an image of that sample is formed. For a small propagation distance, between the exit surface of the sample and the entrance surface of a position-sensitive detector, the paraxial approximation implies that the blurring influence of the sample may be modeled using an anomalous-diffusion field. This diffusion field may have a scalar or tensor character, depending on whether the random microstructure has an autocorrelation function that is rotationally isotropic or anisotropic, respectively. Partial differential equations are written down and then solved, in a closed-form manner, for several variants of the inverse problem of diffusion-field retrieval given suitable intensity images. Both uniform-illumination and structured-illumination schemes are considered. Links are made, between the recovered diffusion field and certain statistical properties of the unresolved microstructure. The developed theory -- which may be viewed as a crudely parallel form of small-angle scattering under the Guinier approximation -- is applicable to a range of paraxial radiation and matter fields, such as visible light, x rays, neutrons, and electrons.

physics.optics↗

arXiv2023

Fast implicit diffusive dark-field retrieval for single-exposure, single-mask x-ray imaging

Complementary to conventional and phase X-ray radiography, dark-field imaging has become central in visualizing diffusive scattering signal due to the spatially-unresolved texture within an object. To date most diffusive-dark-field retrieval methods require either the acquisition of multiple images at the cost of higher radiation dose or significant amounts of computational memory and time. In this work, a simple method of X-ray diffusive dark-field retrieval is presented, applicable to any single-mask imaging setup, with only one exposure of the sample. The approach, which is based on a model of geometric and diffusive reverse-flow conservation, is implicit and non-iterative. This numerically fast methodology is applied to experimental X-ray images acquired using both a random mask and a grid mask, giving high quality reconstructions that are very stable in the presence of noise. The method should be useful for high-speed imaging and/or imaging with low-flux sources.

physics.med-ph↗

arXiv2023

Multimodal Intrinsic Speckle-Tracking (MIST) to extract rapidly-varying diffuse X-ray scatter

Speckle-based phase-contrast X-ray imaging (SB-PCXI) can reconstruct high-resolution images of weakly-attenuating materials that would otherwise be indistinguishable in conventional attenuation-based imaging. The experimental setup of SB-PCXI requires only a sufficiently coherent source and spatially random mask, positioned between the source and detector. The technique can extract sample information at length scales smaller than the imaging system's spatial resolution; this enables multimodal signal reconstruction. ``Multimodal Intrinsic Speckle-Tracking'' (MIST) is a rapid and deterministic formalism derived from the paraxial-optics form of the Fokker-Planck equation. MIST simultaneously extracts attenuation, refraction, and small-angle scattering (diffusive-dark-field) signals from a sample and is more computationally efficient compared to alternative speckle-tracking approaches. Hitherto, variants of MIST have assumed the diffusive-dark-field signal to be spatially slowly varying. Although successful, these approaches have been unable to well-describe unresolved sample microstructure whose statistical form is not spatially slowly varying. Here, we extend the MIST formalism such that there is no such restriction, in terms of a sample's rotationally-isotropic diffusive-dark-field signal. We reconstruct multimodal signals of two samples, each with distinct X-ray attenuation and scattering properties. The reconstructed diffusive-dark-field signals have superior image quality compared to our previous approaches which assume the diffusive-dark-field to be a slowly varying function of transverse position. Our generalisation may assist increased adoption of SB-PCXI in applications such as engineering and biomedical disciplines, forestry, and palaeontology, and is anticipated to aid the development of speckle-based diffusive-dark-field tensor tomography.

physics.med-ph↗

arXiv2022

Single-exposure x-ray dark-field imaging: quantifying sample microstructure using a single-grid setup

The size of the smallest detectable sample feature in an x-ray imaging system is usually restricted by the spatial resolution of the system. This limitation can now be overcome using the diffusive dark-field signal, which is generated by unresolved phase effects or the ultra-small-angle x-ray scattering from unresolved sample microstructures. A quantitative measure of this dark-field signal can be useful in revealing the microstructure size or material for medical diagnosis, security screening and materials science. Recently, we derived a new method to quantify the diffusive dark-field signal in terms of a scattering angle using a single-exposure grid-based approach. In this manuscript, we look at the problem of quantifying the sample microstructure size from this single-exposure dark-field signal. We do this by quantifying the diffusive dark-field signal produced by 5 different sizes of polystyrene microspheres, ranging from 1.0 $μ$m to 10.8 $μ$m, to investigate how the strength of the dark-field signal changes with the sample microstructure size, $S$. We also explore the feasibility of performing single-exposure dark-field imaging with a simple equation for the optimal propagation distance given microstructure with a specific size and thickness, and successfully verify this equation with experimental data. Our theoretical model predicts that the dark-field scattering angle is inversely proportional to $\sqrt{S}$, which is consistent with our experimental data.

physics.med-ph↗

arXiv2021

Tomographic phase and attenuation extraction for a sample composed of unknown materials using X-ray propagation-based phase-contrast imaging

Propagation-based phase-contrast X-ray imaging (PB-PCXI) generates image contrast by utilizing sample-imposed phase-shifts. This has proven useful when imaging weakly-attenuating samples, as conventional attenuation-based imaging does not always provide adequate contrast. We present a PB-PCXI algorithm capable of extracting the X-ray attenuation, $β$, and refraction, $δ$, components of the complex refractive index of distinct materials within an unknown sample. The method involves curve-fitting an error-function-based model to a phase-retrieved interface in a PB-PCXI tomographic reconstruction, which is obtained when Paganin-type phase-retrieval is applied with incorrect values of $δ$ and $β$. The fit parameters can then be used to calculate true $δ$ and $β$ values for composite materials. This approach requires no a priori sample information, making it broadly applicable. Our PB-PCXI reconstruction is single distance, requiring only one exposure per tomographic angle, which is important for radiosensitive samples. We apply this approach to a breast-tissue sample, recovering the refraction component, $δ$, with 0.6 - 2.4\% accuracy compared to theoretical values.

physics.med-ph↗

arXiv2021

Directional dark-field implicit x-ray speckle tracking using an anisotropic-diffusion Fokker-Planck equation

When a macroscopic-sized non-crystalline sample is illuminated using coherent x-ray radiation, a bifurcation of photon energy flow may occur. The coarse-grained complex refractive index of the sample may be considered to attenuate and refract the incident coherent beam, leading to a coherent component of the transmitted beam. Spatially-unresolved sample microstructure, associated with the fine-grained components of the complex refractive index, introduces a diffuse component to the transmitted beam. This diffuse photon-scattering channel may be viewed in terms of position-dependent fans of ultra-small-angle x-ray scatter. These position-dependent fans, at the exit surface of the object, may under certain circumstances be approximated as having a locally-elliptical shape. By using an anisotropic-diffusion Fokker-Planck approach to model this bifurcated x-ray energy flow, we show how all three components (attenuation, refraction and locally-elliptical diffuse scatter) may be recovered. This is done via x-ray speckle tracking, in which the sample is illuminated with spatially-random x-ray fields generated by coherent illumination of a spatially-random membrane. The theory is developed, and then successfully applied to experimental x-ray data.

physics.med-ph↗