Dark-field imaging on a clinical CT system: sample data processing and reconstruction

Abstract

Grating-based phase-contrast and dark-field X-ray imaging is a promising technology for improving the diagnosis and imaging capabilities of breast cancer and lung diseases. While traditional X-ray techniques only consider the attenuation coefficient, phase-contrast and dark-field imaging are also capable of measuring the refractive index decrement and the so-called linear diffusion coefficient, a measure of a sample’s small-angle scattering strength. Consequently, the technique provides additional information about the micro-structure of a sample. While it is already possible to perform human chest dark-field radiography, it is assumed that its diagnostic value increases when performed in a tomographic setup. The thereby acquired three-dimensional mappings of the three modalities yield detailed information about morphological changes without being obscured by overlaying structures. This work presents the sample data processing and reconstruction pipeline of the first human-sized clinical dark-field CT system. In this novel setting we require a processing concept which is (1) compatible with continuous rotation, (2) can compensate for perturbances induced by system vibrations, and (3) still enables short processing and reconstruction times. An advanced sliding window approach was chosen for the sample data extraction to meet requirements (1) and (3). Furthermore, we present the corrective measures that have to be applied in the employed processing and reconstruction algorithms to mitigate the effects of vibrations and deformations of the interferometer gratings. The developed techniques are shown to successfully reduce the emergence of artefacts in the reconstructed images.