Rich and Non-rich Tomography with the Core Imaging Library

Learn about rich and non-rich tomography applications through a seminar presentation that explores the Core Imaging Library (CIL), a Python package designed for solving complex tomography and inverse problems. Discover recent developments in hyperspectral neutron tomography, including spatio-spectral reconstruction methods for material separation using Bragg edges in energy-resolved neutron data. Examine a directional total variation reconstruction method for limited-angle X-ray CT reconstruction, which was submitted to the Helsinki Tomography Challenge 2022. Gain insights into how CIL facilitates the integration of mathematics, algorithms, and numerical software to address challenging tomography problems, with opportunities to apply these tools to personal research through upcoming training and hackathon events.