Joint image reconstruction of multi-channel X-ray computed tomography data for material scienceMS68

Rapidly developing technology of photon-counting or energy-discriminating detectors has provided an additional spectral dimension to conventional X-ray grayscale imaging.The energy-binned data, however, suffer from low signal-to-noise ratio, acquisition artifacts, and frequently angular undersampled conditions. Since energy-channels are mutually correlated it can be advantageous to incorporate additional knowledge into the reconstruction algorithm. We propose a novel iterative method which jointly reconstructs all energy channels while imposing a strong structural correlation between them.

This presentation is part of Minisymposium “MS68 - Multi-channel image reconstruction approaches
organized by: Jakob Jorgensen (University of Manchester) , Daniil Kazantsev (University of Manchester) .

Daniil Kazantsev (University of Manchester)
computed tomography, image enhancement, image reconstruction, inverse problems