MS 15: Towards Robust Tomography

Fri, 31 March, 2017, 13:30–15:30, Room: UC 202DH


Samuli Siltanen


Defects and gaps in tomographic data can cause severe artefacts in the reconstructions. However, many practical imaging situations lead to badly calibrated or sparsely collected data. Sometimes only a region of interest can be properly imaged, while surrounding areas are undersampled. Among the methods for reducing artefacts are utilizing the redundancy in the Radon transform, and applying strong regularization techniques. In this minisymposium, various methods are discussed for tomographic imaging robust against modelling errors, data noise, and undersampling.

List of speakers

Tatiana Bubba
Iterative $\ell_1$ shearlet regularization for the ROI tomography problem
Andreas Hauptmann
A Variational Reconstruction Method for Dynamical X-ray Tomography based on Physical Motion Models
Federica Marone
Synchrotron based X-ray tomographic microscopy: A compromise between theory and practise
Zenith Purisha
Three-dimensional reconstruction of a human trabecular bone using sparse x-ray tomography
Simon Maretzke
Generalized SART-methods for robust and efficient tomography