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DC poleHodnotaJazyk
dc.contributor.authorDulau, Idris
dc.contributor.authorBeurton-Aimar, Marie
dc.contributor.authorHwu, Yeykuang
dc.contributor.authorRecur, Benoit
dc.contributor.editorSkala, Václav
dc.date.accessioned2023-10-15T12:54:31Z
dc.date.available2023-10-15T12:54:31Z
dc.date.issued2023
dc.identifier.citationWSCG 2023: full papers proceedings: 1. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 11-19.en
dc.identifier.isbn978-80-86943-32-9
dc.identifier.issn2464–4617 (print)
dc.identifier.issn2464–4625 (CD/DVD)
dc.identifier.urihttp://hdl.handle.net/11025/54394
dc.format9 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.rights© Václav Skala - UNION Agencyen
dc.subjectrentgenová nanotomografiecs
dc.subjectsegmentacecs
dc.subjecthluboké učenícs
dc.subjectzobrazování mozkucs
dc.titleInvestigation on Encoder-Decoder Networks for Segmentation of Very Degraded X-Ray CT Tomogramsen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedField of View (FOV) Nano-CT X-Ray synchrotron imaging is used for acquiring brain neuronal features from Golgi-stained bio-samples. It theoretically requires a large number of acquired data for compensating CT recon struction noise and artefacts (both reinforced by the sparsity of brain features). However reducing the number of radiographs is essential in routine applications but it results to degraded tomograms. In such a case, traditional segmentation techniques are no longer able to distinguish neuronal structures from surrounding noise. Thus, we investigate several deep-learning networks to segment brain features from very degraded tomograms. We focus on encoder-decoder networks and define new ones addressing specifically our application. We demonstrate that some networks wildly outperform traditional segmentation and discuss the superiority of the proposed networks.en
dc.subject.translatedX-Ray nano-tomographyen
dc.subject.translatedsegmentationen
dc.subject.translateddeep-learningen
dc.subject.translatedbrain imagingen
dc.identifier.doihttps://www.doi.org/10.24132/CSRN.3301.3
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:WSCG 2023: Full Papers Proceedings

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