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Lorenzo Massimi

Publications and source records attributed to Lorenzo Massimi.

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Retrieval of multiple fibre orientations using X-ray dark-field signal modelling

Dark-field imaging is widely used to infer fibre orientation from signal modulation as a function of sample orientation. However, current X-ray dark-field retrieval methods are restricted to single orientations and require tomography to resolve overlapping structures. This approach is time-consuming and not suitable for thin materials, which are common in materials science. Here we present a dark-field model capable of retrieving multiple fibre orientations within a single pixel. The model, based on a geometrical description of fibre scattering, was validated through Monte Carlo simulations and experiments using beam-tracking setups with 1D and 2D masks. Results demonstrate reliable orientation retrieval for up to two fibres per pixel, with the 2D mask providing multi-directional sensitivity in a single acquisition and enabling faster and simplified data collection.

physics.med-ph

Accelerated iterative tomographic reconstruction with x-ray edge illumination

Compared to standard tomographic reconstruction, iterative approaches offer the possibility to account for extraneous experimental influences, which allows for a suppression of related artifacts. However, the inclusion of corresponding parameters in the iterative forward model typically leads to longer computation times. Here, we demonstrate experimentally for phase sensitive X-ray imaging based on the edge illumination principle that inadequately sampled illumination curves result in ring artifacts in tomographic reconstructions. We take advantage of appropriately sampled illumination curves instead, which enables us to eliminate the corresponding parameter from the forward model and substantially increase computational speed. In addition, we demonstrate a 30\% improvement in spatial resolution of the iterative approach compared with the standard non-iterative single shot approach. Further, we report on several significant improvements in our numerical implementation of the iterative approach, which we make available online with this publication. Finally, we show that the combination of both experimental and algorithmic advancement lead to a total speed increase by one order of magnitude and an improved contrast to noise ratio in the reconstructions.

eess.IV