Single-shot, high sensitivity X-ray phase contrast imaging system based on a Hartmann mask

There is currently much interest in developing X-ray Phase Contrast Imaging (XPCI) systems which employ laboratory sources in order to deploy the technique in real world applications. The challenge faced by nearly all XPCI techniques is that of efficiently utilising the x-ray flux emitted by an x-ray tube which is polychromatic and possesses only partial spatial coherence. Techniques have, however, been developed which overcome these limitations. Such a technique, known as coded aperture XPCI, has been under development in our laboratories in recent years for application principally in medical imaging and security screening. In this paper we derive limitations imposed upon source polychromaticity and spatial extent by the coded aperture system. We also show that although other grating XPCI techniques employ a different physical principle, they satisfy design constraints similar to those of the coded aperture XPCI.

It is hoped that x-ray phase contrast imaging (XPCi) will provide a generational improvement in the effectiveness of mammography. XPCi is sensitive to the refraction which x-rays undergo as a result of the variation in x-ray propagation speeds within an object. XPCi is, however, seldom used in clinical applications owing mainly to a lack of suitable systems. The radiation physics group at UCL has previously designed and built an XPCi system sensitive to phase gradients in one dimension for application in security inspection. We present here the design methodology and final design of a prototype XPCi system sensitive to phase gradients in two directions for use in mammography. The technique makes efficient use of the flux available from a laboratory x-ray source, thus making it suitable for clinical use.

The development of interferometry-based X-ray phase contrast imaging systems that provide highly resolved X-rays with spatially-modulated intensity is enabling the full potential of X-ray optics to image phase, attenuation, and small angle scatter properties of soft tissue. In this work we present analytical formulations of a new hardware concept for X-ray phase contrast imaging wherein the phase grating is replaced with an array of Fresnel biprisms. We derive expressions for the irradiance distribution pattern of a biprism interferometer composed of a curved biprism array with multiple biprisms and multiple point sources. These expressions are used to plot fringe patterns for X-ray design parameters, including 1) size, number, and period of X-ray point sources; 2) biprism parameters of material composition, angle, number, and period; and 3) biprism array to X-ray source and detector distances. Analytical results show that the biprism interferometer provides a longitudinally-nonperiodic pattern of spatially modulated intensity different from the Talbot longitudinally-periodic pattern common in grating interferometry. The curvature of the biprism array brings a sharper longitudinal fringe pattern. Experiments are being performed to verify the analytical calculations for a biprism plastic material of SU-8 using a synchrotron source. X-ray biprism material has widely varied indexes of refraction relative to wavelength and thus the separation of the virtual sources and resulting interference fringe period also varies with X-ray wavelength. Our aim is to develop biprism interferometry imaging systems with excellent polychromatic performance that produce high-contrast fringes with spatially incoherent X-ray illumination. Biprism interferometry will potentially provide higher fringe visibility with better image quality to that of diffraction grating interferometry.

Hybrid framework for feasible modeling of an edge illumination X-ray phase-contrast imaging system at a human scale

Significant efforts are currently ongoing in X-ray imaging to provide multimodal imaging systems, targeting better sensitivity and specificity for both biomedical or non-destructive testing applications. Knowing the elemental composition of specific structures, such as breast microcalcifications in mammography, would help to differentiate malign and benign tumours. Standard X-ray Phase Contrast Imaging techniques provide only qualitative information on elements with similar absorption properties. However, their chemical composition can be determined from the measurement of the phase as it is directly related to the optical index of elemental materials. We will show new experimental results obtained with an X-ray phase imaging system based on a Hartmann mask. Early data treatment succeeded in retrieving both the real and imaginary parts of the refractive index. The system demonstrates the capability to discriminate materials based on elemental composition.

Phase retrieval for X-ray differential phase contrast radiography with knowledge transfer learning from virtual differential absorption model

3D ultrasound imaging is becoming increasingly prevalent in the medical field. Compared to conventional 2D imaging systems, 3D imaging can provide a detailed view of tissue structures that makes diagnosis easier for the physicians. In addition, 2D image slices can be formed at various orientations to the transducer, making the examination less dependent on the skill of the sonographer. However, various challenges exist in developing a 3D imaging system, such as integration of a large number of elements, as well as post-processing of datasets received from a large number of channels. 2D transducer arrays are typically integrated with custom ICs in the probe handle to perform some intermediate beamforming and to reduce the number of cable connections to the imaging system. Capacitive micromachined ultrasonic transducers (CMUTs) have emerged as an alternative to piezoelectric transducers. Being a MEMS device, they greatly benefit from flexibility and ease of fabrication, and can be seamlessly integrated with electronics. Previous work demonstrates 3D stacking of CMUTs and dummy ICs with an intermediate interposer layer. However, that represents more of a mechanical demonstration of 3D integration. In this paper, we present a fully functional 3D ultrasound imaging system comprising a 32×32 2D CMUT array, 3D-stacked with front-end ICs using flip-chip bonding technology. The imaging system is capable of capturing real-time volumetric ultrasound data, and displaying 2D and 3D ultrasound images.

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.

Abstract. As remote sensing and variable-rate technology are becoming more available for aerial applicators, practical methodologies for effective integration of these technologies are needed for site-specific aerial applications of crop production and protection materials. The objectives of this study were to demonstrate how to integrate an airborne multispectral imaging system and an IntelliStar variable-rate aerial application system for site-specific management of the winter weed henbit. The airborne imaging system was used to acquire natural color and near-infrared (NIR) images of a fallow field near College Station, Texas, for mapping the infestation of henbit shortly before herbicide application. The images were then rectified, classified, and converted to a binary prescription map with the full application rate on infested areas and the zero rate on non-infested areas. The variable-rate aerial application system mounted on an agricultural aircraft was used to apply glyphosate over the field based on the prescription map. Airborne imagery was collected 14 days after the herbicide application. The as-applied map along with the prescription map and the post-application imagery were used to assess the performance of the site-specific application. Spatial and statistical analysis results showed that the imaging system was effective for mapping henbit infestations and for assessing the performance of site-specific herbicide application, and that the variable-rate system accurately delivered the product at the desired rate to the prescribed areas for effective control of the weed. The methodology and results from this study will be useful for aerial applicators to incorporate airborne imaging and variable-rate application systems into their aerial application business to increase their capabilities and profits. Keywords: Aerial application, As-applied map, Henbit, Imaging system, Prescription map, Variable-rate technology.

This study leverages x‐ray phase‐contrast tomography (XPCT) for detailed analysis of neurodegenerative diseases, focusing on the three‐dimensional (3D) visualization and quantification of neuropathological features within fixed human postmortem tissue. XPCT with synchrotron radiation offers micrometer and even sub‐micron resolution, enabling us to examine intra‐ and extraneuronal aggregates and inclusions such as Lewy bodies (LBs), granulovacuolar degeneration (GvD), Hirano bodies (HBs), neurofibrillary tangles (NFTs), β‐amyloid plaques, and vascular amyloid deposits in three dimensions. In the reconstructions, we identified the highest electron densities in Hirano and LBs, while NFTs exhibited no significant increase in XPCT contrast. Using cutting‐edge high‐resolution x‐ray synchrotron beamlines, we were now able to detect even detect subcellular differences in electron densities found in GvD. Small‐scale inhomogeneities of the electron density were also detected in LBs, potentially relating to inclusions of organelles. Additionally, we reveal here a peculiar 3D geometry of HBs and demonstrate the co‐occurrence with GvD in the same neuron. These findings underscore the potential of XPCT as a powerful, label‐free tool for spatially resolved neuropathological investigations, opening new avenues for the systematic 3D characterization of inclusions and aggregates in neurodegeneration.

X-ray phase contrast imaging (XPCI) can separate the attenuation, refraction, and scattering signals of the object. The application of image fusion enables the concentration of distinctive information into a single image. Some methods have been applied in XPCI field, but wavelet-based decomposition approaches often result in loss of original data. To explore the application value of a novel image fusion method for XPCI system and computed tomography (CT) system. The means of fast adaptive bidimensional empirical mode decomposition (FABEMD) is considered for image decomposition to avoid unnecessary information loss. A parameter δ is proposed to guide the fusion of bidimensional intrinsic mode functions which contain high-frequency information, using a pulse coupled neural network with morphological gradients (MGPCNN). The residual images are fused by the energy attribute fusion strategy. Image preprocessing and enhancement are performed on the result to ensure its quality. The effectiveness of other image fusion methods has been compared, such as discrete wavelet transforms and anisotropic diffusion fusion. The δ-guided FABEMD-MGPCNN method achieved either the first or second position in objective evaluation metrics with biological samples, as compared to other image fusion methods. Moreover, comparisons are made with other fusion methods used for XPCI. Finally, the proposed method applied in CT show expected results to retain the feature information. The proposed δ-guided FABEMD-MGPCNN method shows potential feasibility and superiority over traditional and recent image fusion methods for X-ray differential phase contrast imaging and computed tomography systems.

Medical images are acquired for the purpose of gathering information regarding the disease state of a patient. The quality of the image should be a measure of how a specified task may be performed given the resulting image. Image quality is task dependent; one imaging system may provide images that allow better task performance than another system's for one task, but worse for another task. Determining the quality of an imaging system involves specifying the task of interest, the range of objects that will be imaged, and the observer (human or machine reader) who will perform the task. In radiography it has become common to use Fourier measures to describe image quality through a combination of Fourier‐based measures of system resolution and noise. The Line Spread Function, when Fourier transformed, yields the Modulation Transfer Function (MTF) as a measure of system resolution. Use of the MTF to describe a system's resolution is appropriate when the imaging system is shift‐invariant, that is, the line spread function is independent of position. Image noise is described in the Fourier domain by the Noise Power Spectrum (NPS). We can use the NPS to describe the noise in an imaging system whenever the noise properties are stationary, meaning that the variance and correlations between fluctuations in different locations are not dependent on their absolute location. These Fourier measures of system resolution and noise are commonly combined to give an overall figure of merit known as the Detective Quantum Efficiency (DQE). The DQE describes the signal‐to‐noise transfer characteristics of an imaging system as long as those assumptions of shift‐invariance and noise stationarity are valid. In digital systems the image of an object is affected by the location of the object with respect to the pixel grid. In other words, the detector pixels cause the system to be shift‐variant. In this case the MTF does not describe the resolution properties completely. This is particularly the case for tomographic systems, where the point‐response function is quite position‐dependent. Moreover, in real imaging systems the noise properties will depend on position, most notably because real patients always have structure. So, the Fourier‐domain noise concept of Noise Power Spectrum does not capture all the properties of noise for real imaging systems and tasks. In this talk we will consider a general treatment of the imaging system as a mapping of information from the patient to the data, without the assumptions inherent in Fourier analysis. We will discuss approaches to the characterization of system resolution and noise in terms of position‐dependent parameters. Once such position‐dependent imaging properties of a system are determined, we can use them to calculate measures of image quality that summarize the usefulness of the images for the performance of various visual tasks.

A simple multispectral classification method for the identification of systemically diseased chickens was developed and tested between two different imaging systems. An image processing algorithm was developed to define and locate the region of interest (ROI) as classification areas on the image. The average intensity was calculated for each classification area of the chicken image. A decision tree algorithm was used to determine threshold values for each classification areas. The wavelength of 540 nm was used for image differentiation purpose. There were 164 wholesome and 176 systemically diseased chicken images collected using the first imaging system, and 332 wholesome and 318 systemically diseased chicken images taken by the second imaging system. The differentiation thresholds, generated by the decision tree method, based on the images from the first imaging system were applied to the images from the second imaging system, and vice versa. The accuracy from evaluation was 95.7% for wholesome and 97.7% of systemically diseased chickens for the first image batch, and 99.7% for wholesome and 93.5% for systemically diseased chickens for the second image batch. The result showed that using single wavelength and threshold, this simple classification method can be used in automated on-line applications for chicken inspection.

Imaging systems using aspheric imaging lenses with complementary computation can deliver performance unobtainable in conventional imaging systems. These new imaging systems, termed Wavefront coded imaging systems, use specialized optics to capture a coded image of the scene. Decoding the intermediate image provides the "human-usable" image expected of an imaging system. Computation for the decoding step can be made completely transparent to the user with today's technology. Real-time Wavefront coded systems are feasible and cost-effective. This "computational imaging" technology can be adapted to solve a wide range of imaging problems. Solutions include the ability to provide focus-free imaging, to increase the field of view, to increase the depth of read, to correct for aberrations (even in single lens systems), and to account for assembly and temperature induced misalignment. Wavefront coded imaging has been demonstrated across a wide range of applications, including microscopy, miniature cameras, machine vision systems, infrared imaging systems and telescopes.

Due to the enormous advances made in semiconductor technology over the last few years, high integration densities with moderate costs are achievable even in the millimeter-wave (mm-wave) range and beyond, which encourage the development of imaging systems with a high number of channels. The mm-wave range lies between 30 and 300 GHz, with corresponding wavelengths between 10 and 1 mm. While imaging objects with signals of a few millimeters in wavelength, many optically opaque objects appear transparent, making mm-wave imaging attractive for a wide variety of commercial and scientific applications like nondestructive testing (NDT), material characterization, security scanning, and medical screening. The spatial resolution in lateral and range directions as well as the image dynamic range offered by an imaging system are considered the main measures of performance. With the availability of more channels combined with the powerful digital signal processing (DSP) capabilities of modern computers, the performance of mm-wave imaging systems is advancing rapidly.