X-ray attenuation models to account for beam hardening in computed tomography.

We introduce a beam-hardening correction method for lab-based X-ray computed tomography (CT) by modifying existing iterative tomographic reconstruction algorithms. Our method simplifies the standard Alvarez-Macovski X-ray attenuation model [Phys. Med. Biol.21, 733 (1976)] and is compatible with conventional (i.e., single-spectrum) CT scans. The sole modification involves a polychromatic projection operation, which is equivalent to applying a weighting that more closely matches the attenuation of polychromatic X-rays. Practicality is a priority, so we only require information about the X-ray spectrum and some constants relating to material properties. No other changes to the experimental setup or the iterative algorithms are necessary. Using reconstructions of simulations and several large experimental datasets, we show that this method is able to remove or reduce cupping, streaking, and other artefacts from X-ray beam hardening and improve the self-consistency of projected attenuation in CT. When the assumptions made in the simplifications are valid, the reconstructed tomogram can even be quantitative.

The binary dissector: phase contrast tomography of two- and three-material objects from few projections.

In X-ray computed tomography (CT) increased information requirements (e.g. increased resolution) typically lead to a concurrent increase in the required number of viewing angles, scanning time and delivered dose. We demonstrate that using phase-contrast imaging it is possible to "dissect" two- and three-material objects into their component materials, which in combination with binary tomographic techniques allows us to satisfy increased information requirements without taking the usual images at additional viewing angles. This imaging scheme reduces the scanning time and dose delivered to samples by at least an order of magnitude when compared to conventional X-ray CT. The effects of noise on our reconstruction scheme are investigated for simulated data. Finally, a slice through a glass tube filled with silica and water is reconstructed from 18 projection images taken on an X-ray ultra Microscope (XuM).

Phase-contrast tomography of single-material objects from few projections.

A method is presented for quantitative polychromatic cone-beam phase-contrast tomographic imaging of a single-material object from few projections. This 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 a priori knowledge reduces the number of required projections, implying significantly reduced dose and scanning time when compared to existing phase-contrast tomography methods. Reconstructions from simulated data sets are used to investigate the effects of noise and establish a minimum required number of projections. An experimental demonstration is then given, using data from a point-projection X-ray microscope. Here, the complex distribution of refractive index in a sample containing several nylon fibers with diameters between 100 microm and 420 microm is reconstructed at a spatial resolution of approximately 4 microm from 20 polychromatic phase-contrast projection images with a mean photon energy of 8.4 keV.