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Directional sinogram inpainting for limited angle tomography
In this paper we propose a new joint model for the reconstruction of
tomography data under limited angle sampling regimes. In many applications of
Tomography, e.g. Electron Microscopy and Mammography, physical limitations on
acquisition lead to regions of data which cannot be sampled. Depending on the
severity of the restriction, reconstructions can contain severe,
characteristic, artefacts. Our model aims to address these artefacts by
inpainting the missing data simultaneously with the reconstruction.
Numerically, this problem naturally evolves to require the minimisation of a
non-convex and non-smooth functional so we review recent work in this topic and
extend results to fit an alternating (block) descent framework. We illustrate
the effectiveness of this approach with numerical experiments on two synthetic
datasets and one Electron Microscopy dataset.Cantab Capital Institute for the Mathematics of Information
PIHC innovation fund of the Technical Medical Centre of UT
Dutch 4TU programme Precision Medicine
Netherlands Organization for Scientific Research (NWO), project 639.073.506
Henslow Research Fellowship at Girton College, Cambridge
Clare College Junior Research Fellowshi