Edge illumination X-ray phase tomography of multi-material samples using a single-image phase retrieval algorithm.

In this paper we present a single-image phase retrieval algorithm for multi-material samples, developed for the edge illumination (EI) X-ray phase contrast imaging method. The theoretical derivation is provided, along with any assumptions made. The algorithm is evaluated quantitatively using both simulated and experimental results from a computed tomography (CT) scan using the EI laboratory implementation. Qualitative CT results are provided for a biological sample containing both bone and soft-tissue. Using a single EI image per projection and knowledge of the complex refractive index, the algorithm can accurately retrieve the interface between a given pair of materials. A composite CT slice can be created by splicing together multiple CT reconstructions, each retrieved for a different pair of materials.

Concept of contrast transfer function for edge illumination x-ray phase-contrast imaging and its comparison with the free-space propagation technique.

Previous studies on edge illumination (EI) X-ray phase-contrast imaging (XPCi) have investigated the nature and amplitude of the signal provided by this technique. However, the response of the imaging system to different object spatial frequencies was never explicitly considered and studied. This is required in order to predict the performance of a given EI setup for different classes of objects. To this scope, in the present work we derive analytical expressions for the contrast transfer function of an EI imaging system, using the approximation of near-field regime, and study its dependence upon the main experimental parameters. We then exploit these results to compare the frequency response of an EI system with respect of that of a free-space propagation XPCi one. The results achieved in this work can be useful for predicting the signals obtainable for different types of objects and also as a basis for new retrieval methods.

Single-image phase retrieval using an edge illumination X-ray phase-contrast imaging setup.

A method is proposed which enables the retrieval of the thickness or of the projected electron density of a sample from a single input image acquired with an edge illumination phase-contrast imaging setup. The method assumes the case of a quasi-homogeneous sample, i.e. a sample with a constant ratio between the real and imaginary parts of its complex refractive index. Compared with current methods based on combining two edge illumination images acquired in different configurations of the setup, this new approach presents advantages in terms of simplicity of acquisition procedure and shorter data collection time, which are very important especially for applications such as computed tomography and dynamical imaging. Furthermore, the fact that phase information is directly extracted, instead of its derivative, can enable a simpler image interpretation and be beneficial for subsequent processing such as segmentation. The method is first theoretically derived and its conditions of applicability defined. Quantitative accuracy in the case of homogeneous objects as well as enhanced image quality for the imaging of complex biological samples are demonstrated through experiments at two synchrotron radiation facilities. The large range of applicability, the robustness against noise and the need for only one input image suggest a high potential for investigations in various research subjects.

Achromatic approach to phase-based multi-modal imaging with conventional X-ray sources.

Compatibility with polychromatic radiation is an important requirement for an imaging system using conventional rotating anode X-ray sources. With a commercially available energy-resolving single-photon-counting detector we investigated how broadband radiation affects the performance of a multi-modal edge-illumination phase-contrast imaging system. The effect of X-ray energy on phase retrieval is presented, and the achromaticity of the method is experimentally demonstrated. Comparison with simulated measurements integrating over the energy spectrum shows that there is no significant loss of image quality due to the use of polychromatic radiation. This means that, to a good approximation, the imaging system exploits radiation in the same way at all energies typically used in hard-X-ray imaging.

On the origin of contrast in edge illumination X-ray phase-contrast imaging.

Edge illumination (EI) has emerged as an X-ray phase-contrast imaging (XPCi) modality which could present significant advantages in terms of translation to clinical and laboratory applications. In this paper, we model its signal through the use of the "transport of intensity" equation. The validity conditions for this approach and its relationship with previous theoretical models for EI XPCi are discussed. The proposed model enables a simple estimation of the different contributions to the signal, which is shown to complement previously obtained results. In particular, it allows taking into account the effect of both slowly and rapidly varying refraction angles, corresponding to large and small object features. The derived framework is then used to investigate the effect on the signal of the smoothness of the mask edges, of the blurring from the source size and of the width of the object edge.

Spatial resolution of edge illumination X-ray phase-contrast imaging.

We analyze the spatial resolution of edge illumination X-ray phase-contrast imaging and its dependence upon various experimental parameters such as source size, source-to-sample and sample-to-detector distances, X-ray energy and size of the beam-shaping aperture. Different propagation regimes, as well as the beam divergence and polychromaticity encountered with laboratory sources, are also considered. We show that spatial resolution in edge illumination phase-contrast imaging presents peculiar features compared to other X-ray phase-contrast techniques. In particular, in the direction orthogonal to the s or mask lines used to shape the beam, this can be better than both the pixel dimension and the projected source size. Numerical simulations based on Fresnel diffraction integrals are presented, which confirm the analytical predictions. The obtained results allow a simple estimation of the spatial resolution for edge-illumination phase imaging in both synchrotron and laboratory setups.

Phase retrieval through a one-dimensional ptychographic engine.

Ptychographic techniques are currently the subject of increasing scientific interest due to their capability to retrieve the complex transmission function of an object at very high resolution. However, they impose a substantial burden in terms of acquisition time and dimension of the scanned area, which limits the range of samples that can be studied. We have developed a new method that combines the ptychographic approach in one direction with Fresnel propagation in the other by employing a strongly asymmetric probe. This enables scanning the sample in one direction only, substantially reducing exposure times while covering a large field of view. This approach sacrifices ptychographic-related resolution in one direction, but removes any limitation on the probe dimension in the direction orthogonal to the scanning, enabling the scan of relatively large objects without compromising exposure times.

Phase-contrast microscopy at high x-ray energy with a laboratory setup.

We report on the design and realization of an x-ray imaging system for quantitative phase-contrast microscopy at high x-ray energy with laboratory-scale instrumentation. Phase and amplitude were separated quantitatively at x-ray energies up to 80 keV with micrometric spatial resolution. The accuracy of the results was tested against numerical simulations, and the spatial resolution was experimentally quantified by measuring a Siemens star phase object. This simple setup should find broad application in those areas of x-ray imaging where high energy and spatial resolution are simultaneously required and in those difficult cases where the sample contains materials with similar x-ray absorption.

Computer-aided diagnosis for phase-contrast X-ray computed tomography: quantitative characterization of human patellar cartilage with high-dimensional geometric features.

Phase-contrast computed tomography (PCI-CT) has shown tremendous potential as an imaging modality for visualizing human cartilage with high spatial resolution. Previous studies have demonstrated the ability of PCI-CT to visualize (1) structural details of the human patellar cartilage matrix and (2) changes to chondrocyte organization induced by osteoarthritis. This study investigates the use of high-dimensional geometric features in characterizing such chondrocyte patterns in the presence or absence of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and statistical features derived from gray-level co-occurrence matrices were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic curve (AUC). SIM-derived geometrical features exhibited the best classification performance (AUC, 0.95 ± 0.06) and were most robust to changes in ROI size. These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated and non-subjective manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

Strategies for efficient and fast wave optics simulation of coded-aperture and other x-ray phase-contrast imaging methods.

We derive a Fourier formulation of coded-aperture x-ray phase-contrast imaging, based on the wave theory of optics in the Fresnel approximation. We use this model to develop a flexible, efficient, and general simulation algorithm that can be easily adapted to other implementations of x-ray phase contrast imaging. Likewise, the algorithm enables a simple extension to 2D aperture designs, different acquisition schemes, etc. Problems related to numerical implementation of the algorithm are analyzed in detail, and simple rules are derived that enable us to avoid or at least mitigate them. Finally, comparisons with experimental data and data obtained with a different simulation algorithm are presented to validate the model and demonstrate its advantages in practical implementations. This also enabled us to demonstrate an increase in computational speed of more than one order of magnitude over a previous algorithm.

Amplification of the phase contrast signal at very high x-ray energies.

X-ray phase contrast imaging is increasingly being used in several fields, both at synchrotron facilities and with laboratory sources, due to its increased sensitivity compared to conventional x-ray methods. One important problem is the development of methods to make it suitable for use at very high x-ray energies, needed in many applications. We show how the edge illumination concept, which stands at the basis of the coded-aperture method, allows achieving hyperintense phase signals at energies close to 100 keV, by showing images of both weak phase objects and highly absorbing fossils with a high iron content.

Recent advances in edge illumination x-ray phase-contrast tomography.

Edge illumination (EI) is an x-ray phase-contrast imaging technique, exploiting sensitivity to x-ray refraction to visualize features, which are often not detected by conventional absorption-based radiography. The method does not require a high degree of spatial coherence and is achromatic and, therefore, can be implemented with both synchrotron radiation and commercial x-ray tubes. Using different retrieval algorithms, information about an object's attenuation, refraction, and scattering properties can be obtained. In recent years, a theoretical framework has been developed that enables EI computed tomography (CT) and, hence, three-dimensional imaging. This review provides a summary of these advances, covering the development of different image acquisition schemes, retrieval approaches, and applications. These developments constitute an integral part in the transformation of EI CT into a widely spread imaging tool for use in a range of fields.

Large field of view, fast and low dose multimodal phase-contrast imaging at high x-ray energy.

X-ray phase contrast imaging (XPCI) is an innovative imaging technique which extends the contrast capabilities of 'conventional' absorption based x-ray systems. However, so far all XPCI implementations have suffered from one or more of the following limitations: low x-ray energies, small field of view (FOV) and long acquisition times. Those limitations relegated XPCI to a 'research-only' technique with an uncertain future in terms of large scale, high impact applications. We recently succeeded in designing, realizing and testing an XPCI system, which achieves significant steps toward simultaneously overcoming these limitations. Our system combines, for the first time, large FOV, high energy and fast scanning. Importantly, it is capable of providing high image quality at low x-ray doses, compatible with or even below those currently used in medical imaging. This extends the use of XPCI to areas which were unpractical or even inaccessible to previous XPCI solutions. We expect this will enable a long overdue translation into application fields such as security screening, industrial inspections and large FOV medical radiography - all with the inherent advantages of the XPCI multimodality.

X-ray phase contrast tomography; proof of principle for post-mortem imaging.

OBJECTIVE: To demonstrate the feasibility of using X-ray phase-contrast tomography to assess internal organs in a post-mortem piglet model, as a possible non-invasive imaging autopsy technique. METHODS: Tomographic images of a new-born piglet were obtained using a free-space propagation X-ray phase-contrast imaging setup at a synchrotron (European Synchrotron Radiation Facility, Grenoble, France). A monochromatic X-ray beam (52 keV) was used in combination with a detector pixel size of 46 × 46 µm(2). A phase-retrieval algorithm was applied to all projections, which were then reconstructed into tomograms using the filtered-back projection algorithm. Images were assessed for diagnostic quality. RESULTS: Images obtained with the free-space propagation setup presented high soft-tissue contrast and sufficient resolution for resolving organ structure. All of the main body organs (heart, lungs, kidneys, liver and intestines) were easily identified and adequately visualized. In addition, grey/white matter differentiation in the cerebellum while still contained within the skull was shown. CONCLUSION: The feasibility of using X-ray phase-contrast tomography as a post-mortem imaging technique in an animal model has been demonstrated. Future studies will focus on translating this experiment to a laboratory-based setup. ADVANCES IN KNOWLEDGE: Appropriate image processing and analysis enable the simultaneous visualization of both soft- and hard-tissue structures in X-ray phase-contrast images of a complex, thick sample.

A single-image retrieval method for edge illumination X-ray phase-contrast imaging: Application and noise analysis.

PURPOSE: Edge illumination (EI) X-ray phase-contrast imaging (XPCI) has been under development at University College London in recent years, and has shown great potential for both laboratory and synchrotron applications. In this work, we propose a new acquisition and processing scheme. Contrary to existing retrieval methods for EI, which require as input two images acquired in different setup configurations, the proposed approach can retrieve an approximate map of the X-ray phase from a single image, thus significantly simplifying the acquisition procedure and reducing data collection times. METHODS: The retrieval method is analytically derived, based on the assumption of a quasi-homogeneous object, i.e. an object featuring a constant ratio between refractive index and absorption coefficient. The noise properties of the input and retrieved images are also theoretically analyzed under the developed formalism. The method is applied to experimental synchrotron images of a biological object. RESULTS: The experimental results show that the method can provide high-quality images, where the "edge" signal typical of XPCI images is transformed to an "area" contrast that enables an easier interpretation of the sample geometry. Moreover, the retrieved images confirm that the method is highly stable against noise. CONCLUSIONS: We anticipate that the developed approach will become the method of choice for a variety of applications of EI XPCI, thanks to its ability to simplify the acquisition procedure and reduce acquisitions time and dose to the sample. Future work will focus on the adaptation of the method to computed tomography and to polychromatic radiation from X-ray tubes.

A method for high-energy, low-dose mammography using edge illumination x-ray phase-contrast imaging.

Since the breast is one of the most radiosensitive organs, mammography is arguably the area where lowering radiation dose is of the uttermost importance. Phase-based x-ray imaging methods can provide opportunities in this sense, since they do not require x-rays to be stopped in tissue for image contrast to be generated. Therefore, x-ray energy can be considerably increased compared to those usually exploited by conventional mammography. In this article we show how a novel, optimized approach can lead to considerable dose reductions. This was achieved by matching the edge-illumination phase method, which reaches very high angular sensitivity also at high x-ray energies, to an appropriate image processing algorithm and to a virtually noise-free detection technology capable of reaching almost 100% efficiency at the same energies. Importantly, while proof-of-concept was obtained at a synchrotron, the method has potential for a translation to conventional sources.

Volumetric quantitative characterization of human patellar cartilage with topological and geometrical features on phase-contrast X-ray computed tomography.

Phase-contrast X-ray computed tomography (PCI-CT) has attracted significant interest in recent years for its ability to provide significantly improved image contrast in low absorbing materials such as soft biological tissue. In the research context of cartilage imaging, previous studies have demonstrated the ability of PCI-CT to visualize structural details of human patellar cartilage matrix and capture changes to chondrocyte organization induced by osteoarthritis. This study evaluates the use of geometrical and topological features for volumetric characterization of such chondrocyte patterns in the presence (or absence) of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and topological features derived from Minkowski Functionals were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). Our results show that the classification performance of SIM-derived geometrical features (AUC: 0.90 ± 0.09) is significantly better than Minkowski Functionals volume (AUC: 0.54 ± 0.02), surface (AUC: 0.72 ± 0.06), mean breadth (AUC: 0.74 ± 0.06) and Euler characteristic (AUC: 0.78 ± 0.04) (p < 10(-4)). These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as diagnostic imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

Integrating dimension reduction and out-of-sample extension in automated classification of ex vivo human patellar cartilage on phase contrast X-ray computed tomography.

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns.

X-ray absorption, phase and dark-field tomography through a beam tracking approach.

We present a development of the beam-tracking approach that allows its implementation in computed tomography. One absorbing mask placed before the sample and a high resolution detector are used to track variations in the beam intensity distribution caused by the sample. Absorption, refraction, and dark-field are retrieved through a multi-Gaussian interpolation of the beam. Standard filtered back projection is used to reconstruct three dimensional maps of the real and imaginary part of the refractive index, and of the dark-field signal. While the method is here demonstrated using synchrotron radiation, its low coherence requirements suggest a possible implementation with laboratory sources.

Volumetric Characterization of Human Patellar Cartilage Matrix on Phase Contrast X-Ray Computed Tomography.

Phase contrast X-ray computed tomography (PCI-CT) has recently emerged as a novel imaging technique that allows visualization of cartilage soft tissue, subsequent examination of chondrocyte patterns, and their correlation to osteoarthritis. Previous studies have shown that 2D texture features are effective at distinguishing between healthy and osteoarthritic regions of interest annotated in the radial zone of cartilage matrix on PCI-CT images. In this study, we further extend the texture analysis to 3D and investigate the ability of volumetric texture features at characterizing chondrocyte patterns in the cartilage matrix for purposes of classification. Here, we extracted volumetric texture features derived from Minkowski Functionals and gray-level co-occurrence matrices (GLCM) from 496 volumes of interest (VOI) annotated on PCI-CT images of human patellar cartilage specimens. The extracted features were then used in a machine-learning task involving support vector regression to classify ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best classification performance was observed with GLCM features correlation (AUC = 0.83 ± 0.06) and homogeneity (AUC = 0.82 ± 0.07), which significantly outperformed all Minkowski Functionals (p < 0.05). These results suggest that such quantitative analysis of chondrocyte patterns in human patellar cartilage matrix involving GLCM-derived statistical features can distinguish between healthy and osteoarthritic tissue with high accuracy.