Semi-automatic teeth segmentation in cone-beam computed tomography by graph-cut with statistical shape priors
dc.contributor.author | Evain, Timothée | |
dc.contributor.author | Ripoche, Xavier | |
dc.contributor.author | Atif, Jamal
HAL ID: 15689 | |
dc.contributor.author | Bloch, Isabelle
HAL ID: 175825 ORCID: 0000-0002-6984-1532 | |
dc.date.accessioned | 2017-04-13T07:47:12Z | |
dc.date.available | 2017-04-13T07:47:12Z | |
dc.date.issued | 2017 | |
dc.identifier.uri | https://basepub.dauphine.fr/handle/123456789/16506 | |
dc.description | April 2017, Melbourne Australia | |
dc.language.iso | en | en |
dc.subject | Medical imaging | |
dc.subject | machine learning | |
dc.subject.ddc | 006.3 | en |
dc.title | Semi-automatic teeth segmentation in cone-beam computed tomography by graph-cut with statistical shape priors | |
dc.type | Communication / Conférence | |
dc.contributor.editoruniversityother | Télécom-ParisTech | |
dc.contributor.editoruniversityother | Carestream Dental | |
dc.description.abstracten | We propose a new semi-automatic framework for tooth segmentation in Cone-Beam Computed Tomography (CBCT) combining shape priors based on a statistical shape model and graph cut optimization. Poor image quality and similarity between tooth and cortical bone intensities are overcome by strong constraints on the shape and on the targeted area. The segmentation quality was assessed on 64 tooth images for which a reference segmentation was available, with an overall Dice coefficient above 0.95 and a global consistency error less than 0.005. | |
dc.identifier.citationpages | 1197-1200 | |
dc.relation.ispartoftitle | 14th IEEE International Symposium on Biomedical Imaging (ISBI) | |
dc.relation.ispartofeditor | Olivier Salvado, Gary Egan | |
dc.relation.ispartofpublname | IEEE Signal Processing Society | |
dc.relation.ispartofpublcity | New York | |
dc.relation.ispartofdate | 2017 | |
dc.contributor.countryeditoruniversityother | FRANCE | |
dc.subject.ddclabel | Intelligence artificielle | en |
dc.relation.ispartofisbn | 978-1-5090-1172-8 | |
dc.relation.forthcoming | oui | en |
dc.identifier.doi | 10.1109/ISBI.2017.7950731 | |
dc.description.ssrncandidate | non | |
dc.description.halcandidate | non | |
dc.description.readership | recherche | |
dc.description.audience | International | |
dc.date.updated | 2017-06-30T13:24:24Z |
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