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dc.contributor.authorTovey, Robert
dc.contributor.authorBenning, Martin
dc.contributor.authorBrune, Christoph
dc.contributor.authorLagerwerf, Marinus J
dc.contributor.authorCollins, Sean Michael
dc.contributor.authorLeary, Rowan K
dc.contributor.authorMidgley, Paul A
dc.contributor.authorSchoenlieb, Carola-Bibiane
dc.date.accessioned2018-09-05T12:43:13Z
dc.date.accessioned2018-11-29T00:30:56Z
dc.date.available2018-09-05T12:43:13Z
dc.date.available2018-11-29T00:30:56Z
dc.identifier.issn0266-5611
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/286057
dc.description.abstractIn 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. \oldtext{We illustrate the effectiveness of this approach with numerical experiments on two synthetic datasets and one Electron Microscopy dataset.} \newtext{We perform numerical experiments on two synthetic datasets and one Electron Microscopy dataset. Our results show consistently that the joint inpainting and reconstruction framework can recover cleaner and more accurate structural information than the current state of the art methods.
dc.publisherIoP
dc.relation.replaceshttps://www.repository.cam.ac.uk/handle/1810/279424
dc.relation.replaces1810/279424
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectmath.OC
dc.subjectmath.OC
dc.titleDirectional Sinogram Inpainting for Limited Angle Tomography
dc.typeArticle
dc.identifier.doi10.17863/CAM.33373
dcterms.dateAccepted2018-11-22
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
rioxxterms.licenseref.startdate2018-11-22
dc.contributor.orcidTovey, Robert [0000-0001-5411-2268]
dc.contributor.orcidBenning, Martin [0000-0002-6203-1350]
dc.contributor.orcidCollins, Sean Michael [0000-0002-5151-6360]
dc.contributor.orcidSchoenlieb, Carola-Bibiane [0000-0003-0099-6306]
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/H023348/1)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/J009539/1)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/M00483X/1)
pubs.funder-project-idLeverhulme Trust (RPG-2015-250)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/N014588/1)
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (691070)
pubs.funder-project-idLeverhulme Trust (ECF-2016-611)
pubs.funder-project-idIsaac Newton Trust (1608(aj))
pubs.funder-project-idAlan Turing Institute (unknown)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/R008779/1)
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (777826)


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International