# MS 15: Towards Robust Tomography

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

Samuli Siltanen

## Abstract

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 BubbaIterative $\ell_1$ shearlet regularization for the ROI tomography problem Andreas HauptmannA Variational Reconstruction Method for Dynamical X-ray Tomography based on Physical Motion Models Federica MaroneSynchrotron based X-ray tomographic microscopy: A compromise between theory and practise Zenith PurishaThree-dimensional reconstruction of a human trabecular bone using sparse x-ray tomography Simon MaretzkeGeneralized SART-methods for robust and efficient tomography