Robust Image Reconstruction Strategy for Multiscalar Holotomography.

Holotomography is an extension of computed tomography where samples with low X-ray absorption can be investigated with higher contrast. In order to achieve this, the imaging system must yield an optical resolution of a few micrometers or less, which reduces the measurement area (field of view = FOV) to a few mm at most. If the sample size, however, exceeds the field of view (called local tomography or region of interest = ROI CT), filter problems arise during the CT reconstruction and phase retrieval in holotomography. In this paper, we will first investigate the practical impact of these filter problems and discuss approximate solutions. Secondly, we will investigate the effectiveness of a technique we call "multiscalar holotomography", where, in addition to the ROI CT, a lower resolution non-ROI CT measurement is recorded. This is used to avoid the filter problems while simultaneously reconstructing a larger part of the sample, albeit with a lower resolution in the additional area.

Correcting multi material artifacts from single material phase retrieved holo-tomograms with a simple 3D Fourier method.

Here we present a method for the removal of multi-material artifacts which occur during the application of a single material phase retrieval procedure to X-ray tomographic data sets. For the phase retrieval we chose the most common method which is the single material filter. The correction method which we describe in the following has been designed for samples consisting of three distinct materials, hence effectively two different material interfaces. Furthermore the material phase with the strongest X-ray interaction needs to show sufficient absorption in order to allow for segmenting this phase through application of a grey value threshold. If these conditions are fulfilled the method is easy to apply through post processing as is shown for the volume images of two sample types.