X-ray diffraction tomography (XRDT) enables material identification throughout a volumetric object. We perform a simulation-based study to analyze how the image quality of a fan beam coded aperture XRDT system depends on the specifications of the detector used to measure the scatter signal. Going beyond simulation, we design and implement an XRDT prototype scanner that operates in near real-time to perform slice-by-slice imaging of a target object. The scanner is consistent with the requirements of airport checkpoint lanes and can run inline with existing transmission-based X-ray scanners.
CZT detectors are primary candidates for many next-generation X-ray imaging systems. These detectors are typically operated in either a high precision, low flux spectroscopy mode or a low precision, high flux photon counting mode. We demonstrate a new detector configuration that enables operation in a high precision, medium flux spectroscopy mode, which opens the potential for a variety of new applications in medical imaging, non-destructive testing and baggage scanning. In particular, we describe the requirements of a coded aperture coherent scattering X-ray system that can perform fast imaging with accurate material discrimination.
Previous realizations of coded-aperture X-ray diffraction tomography (XRDT) techniques based on pencil beams image one line through an object via a single measurement but require raster scanning the object in multiple dimensions. Fan beam approaches are able to image the spatial extent of the object while retaining the ability to do material identification. Building on these approaches we present our system concept and geometry of combining a fan beam with energy sensitive/photon counting detectors and a coded aperture to capture both spatial and spectral information about an object at each voxel. Using our system we image slices via snapshot measurements for four different detector configurations and compare their results.
Coded aperture X-ray diffraction (coherent scatter spectral) imaging provides fast and dose-efficient measurements of the molecular structure of an object. The information provided is spatially-dependent and material-specific, and can be utilized in medical applications requiring material discrimination, such as tumor imaging.
However, current coded aperture coherent scatter spectral imaging system assume a uniformly or weakly attenuating object, and are plagued by image degradation due to non-uniform self-attenuation. We propose accounting
for such non-uniformities in the self-attenuation by utilizing an X-ray computed tomography (CT) image (reconstructed attenuation map). In particular, we present an iterative algorithm for coherent scatter spectral image
reconstruction, which incorporates the attenuation map, at different stages, resulting in more accurate coherent
scatter spectral images in comparison to their uncorrected counterpart. The algorithm is based on a spectrally
grouped edge-preserving regularizer, where the neighborhood edge weights are determined by spatial distances
and attenuation values.