Improved tomographic reconstructions using adaptive time-dependent intensity normalization

The first processing step in synchrotron-based micro-tomography is the normalization of the projection images against the background, also referred to as a white field. Owing to time-dependent variations in illumination and defects in detection sensitivity, the white field is different from the projection background. In this case standard normalization methods introduce ring and wave artefacts into the resulting three-dimensional reconstruction. In this paper the authors propose a new adaptive technique accounting for these variations and allowing one to obtain cleaner normalized data and to suppress ring and wave artefacts. The background is modelled by the product of two time-dependent terms representing the illumination and detection stages. These terms are written as unknown functions, one scaled and shifted along a fixed direction (describing the illumination term) and one translated by an unknown two-dimensional vector (describing the detection term). The proposed method is applied to two sets (a stem Salix variegata and a zebrafish Danio rerio) acquired at the parallel beam of the micro-tomography station 2-BM at the Advanced Photon Source showing significant reductions in both ring and wave artefacts. In principle the method could be used to correct for time-dependent phenomena that affect other tomographic imaging geometries such as cone beam laboratory X-ray computed tomography.