Funding: The project is funded for three years by the MIAI Cluster (Multidisciplinary Institute in Artificial Intelligence)
Location: Grenoble
Keywords: X-ray Dark-field Imaging, Small Angle X-ray Scattering, Computational X-rays, Image
Reconstruction, Deep Learning
Overview: This doctoral project aims to dramatically reduce the acquisition time and computational requirements of small-angle X-ray scattering (SAXS) tensor tomography (SAXS-TT) by using directional dark-field (DDF) tensor tomography enhanced with artificial intelligence at every stage of the measurement and reconstruction pipeline. Because DDF is a full-field technique, we will observe a drastic acquisition time reduction (partly compensated by the number of distances of propagation that be lower than the number of voxels in the image). By integrating AI-driven optimisation of encoding masks, intelligent modelling of forward problems and advanced tensor reconstruction algorithms, we can achieve high-quality nanoscale structural characterisation with significantly reduced experimental overheads.
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