Conventional X-ray CT is not usually sufficient to determine microscopic compositional distributions. A dataconstrained
microstructure modeling (DCM) methodology has been developed which uses multiple CT data sets
acquired with different X-ray spectra, and incorporates them as model constraints. The DCM approach has been applied
to predict the distributions of corrosion inhibitor and filler in a polymer matrix. The DCM-predicted compositional
microstructures have a reasonable agreement with EDX images taken on the sample surface.
We discuss theoretical, experimental and numerical aspects of several new techniques for quantitative phase-contrast tomography using, for example, unfiltered radiation from a polychromatic X-ray microfocus source. The proposed algorithms allow one to reconstruct the three-dimensional distribution of complex refractive index in a sample consisting of one or more constituent materials, given one or more projection images per view angle. If the sample is weakly absorbing or consists predominantly of a single material, these reconstruction algorithms can be simplified and fewer projections may be required for an unambiguous quantitative reconstruction of the spatial distribution of the refractive index. In the case of weakly absorbing samples, the reconstruction algorithm is shown to be achromatic and stable with respect to high-spatial-frequency noise, in contrast to conventional tomography. A variation of the algorithm exploits the natural combination of binary tomography with a phase-retrieval method that makes explicit use of the single-material nature of the sample. Such consistent use of <i>a priori </i>knowledge dramatically reduces the number of required projections, implying significantly reduced dose and scanning time when compared to most alternative phase-contrast tomography methods. Experimental demonstrations are also given, using data from a point-projection X-ray microscope. The refractive index distribution, in test samples of both a polymer fibre scaffold and an adult mouse, is accurately reconstructed from polychromatic phase-contrast data. Applications of the new techniques to rapid non-destructive testing in materials science and biomedical imaging are considered.
X-ray phase-contrast tomographic microimaging is a powerful tool to reveal the internal structure of opaque soft-matter objects that are not easily seen in standard absorption contrast. In such low Z materials, the phase shift of X-rays transmitted can be important as compared to the absorption. An easy experimental set up that exploits refractive contrast formation can deliver images that are providing detailed structural information. Applications are abundant in fields
including polymer science and engineering, biology, biomedical engineering, life sciences, zoology, water treatment and filtration, membrane science, and micro/nanomanufacturing. However, available software for absorptive contrast tomography cannot be simply used for structure retrieval as the contrast forming effect is different. In response, CSIRO has developed a reconstruction code for phase-contrast imaging. Here, we present a quantitative comparison of a micro phantom manufactured at SSLS with the object reconstructed by the code using X-ray images taken at SSLS. The phantom is a 500 μm thick 800 μm diameter cylindrical disk of SU-8 resist having various eccentric cylindrical bores with diameters ranging from 350 μm to 40 μm. Comparison of these parameters that are well known from design and post-manufacturing measurements with reconstructed ones gives encouraging results.
X-ray Microtomography bridges the 3D analysis gap between conventional x-ray tomography and TEM tomography.
The use of a laboratory-based microfocus source opens up the opportunity to gain additional benefits from in-line phase
contrast for enhancing the visibility of fine features, cracks, voids and boundaries in individual views. Coupled with
phase retrieval methods, such images can be used as input to conventional reconstruction algorithms for three
dimensional visualization. Working at high resolution brings challenges of physical stability of the system. Software
approaches to overcoming these difficulties have enabled submicron resolution 3D reconstructions.