arXiv subjects

Timur E. Gureyev

Publications and source records attributed to Timur E. Gureyev.

18 recordsLinked to original sources

arXiv2026

Phase-contrast micro-CT for intra-operative breast tumour margin assessment using a microfocus x-ray source and photon-counting detector

Objective: Intra-operative tumour margin assessment during breast-conserving surgery requires rapid, high-resolution imaging of excised tissue, allowing the surgical team to take appropriate action within a single operation. This study evaluates a custom propagation-based phase-contrast micro-computed tomography (micro-CT) system designed to meet these clinical constraints without specialised optical elements. Methods: The experimental setup pairs a microfocus x-ray source with a photon-counting detector in a cone-beam geometry. We explore how the spatial coherence of the source can provide propagation-based phase contrast -- with no additional specialised optical elements -- and balance this against maximising the x-ray flux of the cone-beam geometry. System performance was evaluated across two anode target materials and filtration configurations at various tube power settings. Imaging capabilities were validated using anthropomorphic breast tissue phantoms and a formalin-fixed paraffin-embedded (FFPE) breast tissue specimen, with reconstructions compared against gold-standard histology. Results: An unfiltered tungsten target operated at 40 kVp yielded optimal image quality. The optimised system achieved high-resolution CT reconstructions of a 5 cm diameter sample with an isotropic voxel size of 40.7 $\upmu\text{m}$ in a scan time of 12 minutes. Reconstructed volumes demonstrated strong visual correlation with corresponding histology slides. Conclusion: Combining a microfocus source with a photon-counting detector enables high-resolution, phase-contrast micro-CT within a clinically viable timeframe, demonstrating strong potential for intra-operative margin assessment.

physics.med-ph↗

arXiv2026

Fast Patient-Specific Breast CT Dosimetry: 22-Fold Acceleration of Monte Carlo MGD Estimation

Accurate patient-specific mean glandular dose (MGD) estimation in breast computed tomography (BCT) requires anatomically realistic models, but high-resolution patient-derived phantoms impose high computational demands on Monte Carlo (MC) dosimetry. We previously developed and validated an EGSnrc-based framework for synchrotron propagation-based phase-contrast BCT (PB-PCT) for the first-in-human study at the Australian Synchrotron. With participant imaging commencing, this study aimed to optimize phantom spatial resolution and MC efficiency while maintaining MGD accuracy, for a rapid patient-specific dosimetry. Four patient-specific heterogeneous breast phantoms with varying volume and glandularity were generated from PB-PCT images of mastectomy specimens acquired at 35 keV. The highest-resolution phantom for each specimen served as the reference. Phantoms were downsampled by increasing in-plane voxel size and slice thickness, and MGD was recalculated using EGSnrc/DOSXYZnrc. A 4.5% difference from reference MGD was adopted as the accuracy criterion. Primary photon histories were then reduced to determine the minimum required for acceptable MC precision. A common voxel size of 0.30 x 0.30 x 3.00 mm3 maintained MGD within 4.5% of reference for all four phantoms while reducing voxel number by approximately 20-31-fold. MGD was more sensitive to in-plane voxel size than slice thickness, supporting anisotropic downsampling. Reduced-resolution phantoms enabled a 15-fold reduction in photon histories to 2 x 10^8 while maintaining acceptable statistical uncertainty. Combined optimization reduced computation time from approximately 1600 to 72 min, a 22-fold acceleration. Patient-specific phantoms can be substantially downsampled while maintaining MGD accuracy and markedly reducing computational burden. This optimization provides a foundation for future real-time patient-specific BCT dosimetry.

physics.med-ph↗

arXiv2026

Development and Validation of Patient-Specific Monte Carlo Dosimetry for Synchrotron Breast Phase-Contrast CT

This study develops and validates a patient-specific Monte Carlo (MC) dosimetry framework for propagation-based phase-contrast breast CT (BCT) at the Imaging and Medical Beamline (IMBL), ANSTO Australian Synchrotron, for accurate mean glandular dose (MGD) estimation. BCT provides 3D imaging without breast compression, improving comfort and visualization of internal structures for cancer detection. Propagation-based phase contrast improves soft-tissue contrast at equal or lower dose than conventional systems. Accurate dosimetry remains essential for safety and optimisation. Most MC-based MGD studies use non-patient-specific phantoms that ignore anatomical variability, while existing patient-specific methods lack a unified framework. Here, a voxel-based MC framework using EGSnrc was implemented to compute MGD in realistic anthropomorphic breast phantoms derived from synchrotron BCT images. IMBL beam characteristics were used as source inputs. Homogeneous phantoms were also generated to compute air Kerma to MGD conversion coefficients (DgN) for comparison with heterogeneous models. Simulations covered breast height, skin thickness, and photon energies (28 to 38 keV). Results show MGD depends strongly on anatomy and energy. Higher glandular density reduces MGD, while larger breast volume increases dose. A 2 mm increase in skin thickness reduces MGD by 10%. Differences between heterogeneous and homogeneous phantoms show variations in DgN, highlighting the need for anatomical realism. The framework provides a robust basis for patient-specific dosimetry in synchrotron phase-contrast BCT, enabling precise MGD estimation and supporting safe, optimised clinical imaging. This supports improved protocol design and contributes to standardised patient-specific dosimetry for clinical translation across varying breast anatomies and imaging conditions within synchrotron BCT applications.

physics.med-ph↗

arXiv2026

Efficiency limits in in-line imaging

In-line phase-contrast imaging, also known as propagation-based imaging or Gabor holography, is capable of delivering significant gains in image quality, compared to attenuation-based imaging at the same radiation dose. Image quality metrics, including signal-to-noise ratio and spatial resolution, are considered, and their relationship to the amount of Shannon information in the image is discussed. It is demonstrated that it is possible to increase the image quality gain by combining known phase retrieval methods with deconvolution of the point-spread function (PSF) of the imaging system, with the highest gain achieved using the Contrast Transfer Function correction method in combination with the PSF deconvolution. The ultimate limit of this gain is determined by the ratio of the real decrement to the imaginary part of the complex refractive index of the imaged sample. Analytical results for the image quality limits in in-line imaging are obtained using a Gaussian model for the detector PSF. A numerically simulated example confirming the theoretical results is also presented.

physics.optics↗

arXiv2026

On optimization of Paganin's method for propagation-based X-ray phase-contrast imaging and tomography

Paganin's method for image reconstruction in propagation-based phase-contrast X-ray imaging and tomography has enjoyed broad acceptance in recent years, with over one thousand publications citing its use. The present paper discusses approaches to optimization of the method with respect to simple image quality metrics, such as signal-to-noise ratio and spatial resolution, as well as a reference-based metric corresponding to the relative mean squared difference between the reconstructed image and the "ground truth" image that would be obtained in a setup with perfect spatial resolution and no noise. The problem of optimization of the intrinsic regularization parameter of Paganin's method with respect to spatial resolution in the reconstructed image is studied in detail. It is also demonstrated that a combination of Paganin's method with a Tikhonov-regularized deconvolution of the point-spread function of the imaging system can provide significantly higher image quality compared to the standard version of the method. Analytical expressions for some relevant image quality metrics are obtained and compared with results of numerical simulations. Advantages and shortcomings of optimization approaches using a number of different image quality metrics are discussed. The results of this study are expected to be useful in practical X-ray imaging and training of deep machine learning models for image denoising and segmentation.

physics.med-ph↗

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

Towards order of magnitude X-ray dose reduction in breast cancer imaging using phase contrast and deep denoising

Breast cancer is the most frequently diagnosed human cancer in the United States at present. Early detection is crucial for its successful treatment. X-ray mammography and digital breast tomosynthesis are currently the main methods for breast cancer screening. However, both have known limitations in terms of their sensitivity and specificity to breast cancers, while also frequently causing patient discomfort due to the requirement for breast compression. Breast computed tomography is a promising alternative, however, to obtain high-quality images, the X-ray dose needs to be sufficiently high. As the breast is highly radiosensitive, dose reduction is particularly important. Phase-contrast computed tomography (PCT) has been shown to produce higher-quality images at lower doses and has no need for breast compression. It is demonstrated in the present study that, when imaging full fresh mastectomy samples with PCT, deep learning-based image denoising can further reduce the radiation dose by a factor of 16 or more, without any loss of image quality. The image quality has been assessed both in terms of objective metrics, such as spatial resolution and contrast-to-noise ratio, as well as in an observer study by experienced medical imaging specialists and radiologists. This work was carried out in preparation for live patient PCT breast cancer imaging, initially at specialized synchrotron facilities.

physics.med-ph↗

arXiv2024

Comparison of three reconstruction algorithms for low-dose phase-contrast computed tomography of the breast with synchrotron radiation

Three different computed tomography (CT) reconstruction algorithms: Filtered Back Projection (FBP), Unified Tomographic Reconstruction (UTR) and customized Simultaneous Algebraic Reconstruction Technique (cSART), have been systematically compared and evaluated using experimental data from CT scans of ten fresh mastectomy samples collected at the Imaging and Medical beamline of the Australian Synchrotron. All the scans were collected at the mean glandular dose of 2 mGy, using monochromatic X-rays with 32 keV energy, flat-panel detectors with 0.1 mm pixels and 6 meter distance between the rotation stage and the detector. Paganin's phase retrieval method was used in conjunction with all three CT reconstruction algorithms. The reconstructed images were compared in terms of the objective image quality characteristics, including spatial resolution, contrast, signal-to-noise, and contrast-to-noise ratios. The images were also evaluated by seven experienced medical imaging specialists, rating perceptible contrast, sharpness of tissue interfaces, image noise, calcification visibility and overall image quality. Of the three compared algorithms, cSART was clearly superior to UTR and FBP in terms of most measured objective image quality characteristics. At the same time, the results of the subjective quality evaluation consistently favoured the images reconstructed by FBP, followed by UTR, with cSART receiving lower scores on average. We argue that this apparent disagreement between the objective and subjective assessments of image quality can be explained by the importance assigned to image contrast in the subjective assessment, while the signal-to-noise ratio seemed to receive relatively low weighting. This study was conducted in preparation for phase-contrast breast CT imaging of live patients at Australian Synchrotron (Melbourne, Australia).

physics.med-ph↗

arXiv2024

Single-exposure elemental differentiation and texture-sensitive phase-retrieval imaging with a neutron counting micro-channel plate detector

Micro-channel plate (MCP) detectors, when used at pulsed-neutron-source instruments, offer the possibility of high spatial resolution and high contrast imaging with pixel-level spectroscopic information. Here we demonstrate the possibility of multimodal analysis including total neutron cross-section spectra measurements, quantitative material differentiation imaging and texture-sensitive in-line phase imaging, from a single exposure using an MCP detector. This multimodal approach operates in full-field imaging mode, with the neutron transmission spectra acquired at each individual detector pixel. Due to the polychromatic nature of the beam and spectroscopic resolving capability of the detector, no energy scanning is required. Good agreement with the library reference data is demonstrated for neutron cross-section spectra measurements. Two different images corresponding to two selected energy bandwidths are used for elemental differentiation imaging. Moreover, the presence of changes in texture, i.e., preferred grain orientation, in the sample is identified from our phase-retrieval imaging results.

cond-mat.mtrl-sci↗

arXiv2023

Three-dimensional contrast transfer function in phase-contrast tomography

A new method is developed for three-dimensional (3D) reconstruction of multi-material objects using propagation-based X-ray phase-contrast tomography (PB-CT) with phase retrieval via the contrast transfer function (CTF) formalism. The approach differs from conventional PB-CT algorithms that apply phase retrieval on individual two-dimensional (2D) projections. Instead, this method involves performing phase retrieval to the CT-reconstructed volume in 3D. The CTF formalism is further extended to the cases of partially-coherent illumination and strongly absorbing samples. Simulated results demonstrate that the proposed post-reconstruction CTF method provides fast and stable phase retrieval, producing results equivalent to conventional pre-reconstruction 2D CTF phase retrieval. Moreover, it is shown that application can be highly localised to isolated objects of interest, without a significant loss of quality, thus leading to increased computational efficiency. Combined with the extended validity of the CTF to greater propagation distances, this method provides additional advantages over approaches based on the transport-of-intensity equation.

physics.med-ph↗

arXiv2022

Fast unified reconstruction algorithm for conventional, phase-contrast and diffraction tomography

A unified method for three-dimensional reconstruction of objects from transmission images collected at multiple illumination directions is described. The method may be applicable to experimental conditions relevant to absorption-based, phase-contrast or diffraction imaging using X-rays, electrons and other forms of penetrating radiation or matter waves. Both the phase retrieval (also known as contrast transfer function correction) and the effect of Ewald sphere curvature (in the cases with a shallow depth of field and significant in-object diffraction) are incorporated in the proposed algorithm and can be taken into account. Multiple scattering is not treated explicitly, but can be mitigated as a result of angular averaging that constitutes an essential feature of the method. The corresponding numerical algorithm is based on three-dimensional gridding which allows for fast computational implementation, including a straightforward parallelization. The algorithm can be used with any scanning geometry involving plane-wave illumination. A software code implementing the proposed algorithm has been developed, tested on simulated and experimental image data and made publicly available.

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↗

arXiv2019

Spatial resolution, noise and information in the computational-imaging era

Imaging is an important means by which information is gathered regarding the physical world. Spatial resolution and signal-to-noise ratio are underpinning concepts. There is a paucity of rigorous definitions for these quantities, which are general enough to be useful in a broad range of imaging problems, while being also sufficiently specific to enable precise quantitative evaluation of the relevant properties of imaging systems. This is particularly true for many modern forms of imaging that include digital processing of the acquired imaging data as an integral step leading to final images presented to an end-user. Here, both the well-known historical definitions of spatial resolution and some more recent approaches suitable for many forms of modern computational imaging are discussed. An intrinsic duality of spatial resolution and signal-to-noise exists in almost all types of imaging, with the related uncertainty relationship determining a trade-off between the two quantities. Examples are presented with applications to super-resolution imaging, inline holography and ghost imaging.

physics.optics↗

arXiv2019

Noise-resolution uncertainty principle in classical and quantum systems

It is proved that the width of a function and the width of the distribution of its values cannot be made arbitrarily small simultaneously. In the case of ergodic stochastic processes, an ensuing uncertainty relationship is demonstrated for the product of correlation length and variance. A closely related uncertainty principle is also established for the average degree of fourth-order coherence and the spatial width of modes of bosonic quantum fields. However, it is shown that, in the case of stochastic and quantum observables, certain non-classical states with sub-Poissonian statistics, such as for example photon number squeezed states in quantum optics, can overcome the "classical" noise-resolution uncertainty limit. The described uncertainty relationship, which is fundamentally different from the Heisenberg and related uncertainty principles, can define an upper limit for the information capacity of communication and imaging systems. It is expected to be useful in a variety of problems in classical and quantum physics.

cond-mat.stat-mech↗

arXiv2017

On the van Cittert - Zernike theorem for intensity correlations and its applications

A reciprocal relationship between the autocovariance of the light intensity in the source plane and in the far-field detector plane is presented in a form analogous to the classical van Cittert - Zernike theorem, but involving intensity correlation functions. A "classical" version of the reciprocity relationship is considered first, based on the assumption of circular Gaussian statistics of the complex amplitudes in the source plane. The result is consistent with the theory of Hanbury Brown - Twiss interferometry, but it is shown to be also applicable to estimation of the source size or the spatial resolution of the detector from the noise power spectrum of flat-field images. An alternative version of the van Cittert - Zernike theorem for intensity correlations is then derived for a quantized electromagnetic beam in a coherent state, which leads to Poisson statistics for the intrinsic intensity of the beam.

physics.optics↗

arXiv2017

CT dose reduction factors in the thousands using X-ray phase contrast

Phase-contrast X-ray imaging can improve the visibility of weakly absorbing objects (e.g. soft tissues) by an order of magnitude or more compared to conventional radiographs. Previously, it has been shown that combining phase retrieval with computed tomography (CT) can increase the signal-to-noise ratio (SNR) by up to two orders of magnitude over conventional CT at the same radiation dose, without loss of image quality. Our experiments reveal that as radiation dose decreases, the relative improvement in SNR increases. We discovered this enhancement can be traded for a reduction in dose greater than the square of the gain in SNR. Upon reducing the dose 300 fold, the phase-retrieved SNR was still almost 10 times larger than the absorption contrast data. This reveals the potential for dose reduction factors in the tens of thousands without loss in image quality, which would have a profound impact on medical and industrial imaging applications.

physics.med-ph↗

arXiv2016

On noise-resolution uncertainty in quantum field theory

An uncertainty inequality is presented that establishes a lower limit for the product of the variance of the time-averaged intensity of a mode of a quantized electromagnetic field and the degree of its spatial localization. The lower limit is determined by the vacuum fluctuations within the volume corresponding to the width of the mode. This result also leads to a generalized form of the Heisenberg uncertainty principle for boson fields in which the lower limit for the product of uncertainties in the spatial and momentum localization of a mode is equal to the product of Planck's constant and a dimensionless functional which reflects the joint signal-to-noise ratio of the position and momentum of vacuum fluctuations in the region of the phase space occupied by the mode. Experimental X-ray synchrotron measurements provide an initial verification of the proposed theory in the case of Poisson statistics.

quant-ph↗

arXiv2014

Evaluation of Spatial Resolution and Noise Sensitivity of sLORETA Method for EEG Source Localization Using Low-Density Headsets

Electroencephalography (EEG) has enjoyed considerable attention over the past century and has been applied for diagnosis of epilepsy, stroke, traumatic brain injury and other disorders where 3D localization of electrical activity in the brain is potentially of great diagnostic value. In this study we evaluate the precision and accuracy of spatial localization of electrical activity in the brain delivered by a popular reconstruction technique sLORETA applied to EEG data collected by two commonly used low-density headsets with 14 and 19 measurement channels, respectively. Numerical experiments were performed for a realistic head model obtained by segmentation of MRI images. The EEG source localization study was conducted with a simulated single active dipole, as well as with two spatially separated simultaneously active dipoles, as a function of dipole positions across the neocortex, with several different noise levels in the EEG signals registered on the scalp. The results indicate that while the reconstruction accuracy and precision of the sLORETA method are consistently high in the case of a single active dipole, even with the low-resolution EEG configurations considered in the present study, successful localization is much more problematic in the case of two simultaneously active dipoles. The quantitative analysis of the width of the reconstructed distributions of the electrical activity allows us to specify the lower bound for the spatial resolution of the sLORETA-based 3D source localization in the considered cases.

physics.med-ph↗