Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/52260
DC FieldValueLanguage
dc.contributor.authorKrissian , Karlen_US
dc.contributor.authorCarreira, Jose M.en_US
dc.contributor.authorEsclarin, Julioen_US
dc.contributor.authorMaynar, Manuelen_US
dc.date.accessioned2018-11-25T18:48:01Z-
dc.date.available2018-11-25T18:48:01Z-
dc.date.issued2014en_US
dc.identifier.issn1361-8415en_US
dc.identifier.urihttp://hdl.handle.net/10553/52260-
dc.description.abstractAorta dissection is a serious vascular disease produced by a rupture of the tunica intima of the vessel wall that can be lethal to the patient. The related diagnosis is strongly based on images, where the multi-detector CT is the most generally used modality. We aim at developing a semi-automatic segmentation tool for aorta dissections, which will isolate the dissection (or flap) from the rest of the vascular structure. The proposed method is based on different stages, the first one being the semi-automatic extraction of the aorta centerline and its main branches, allowing an subsequent automatic segmentation of the outer wall of the aorta, based on a geodesic level set framework. This segmentation is then followed by an extraction the center of the dissected wall as a 3D mesh using an original algorithm based on the zero crossing of two vector fields. Our method has been applied to five datasets from three patients with chronic aortic dissection. The comparison with manually segmented dissections shows an average absolute distance value of about half a voxel. We believe that the proposed method, which tries to solve a problem that has attracted little attention to the medical image processing community, provides a new and interesting tool to isolate the intimal flap that can provide very useful information to the clinician.en_US
dc.languageengen_US
dc.relation.ispartofMedical Image Analysisen_US
dc.sourceMedical Image Analysis [ISSN 1361-8415], v. 18 (1), p. 83-102en_US
dc.subject1203 Ciencia de los ordenadoresen_US
dc.subject.otherAortaen_US
dc.subject.otherComputed tomographyen_US
dc.subject.otherDissection wallen_US
dc.subject.otherVessel segmentationen_US
dc.titleSemi-automatic segmentation and detection of aorta dissection wall in MDCT angiographyen_US
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeArticlees
dc.identifier.doi10.1016/j.media.2013.09.004
dc.identifier.scopus84886261951-
dc.identifier.isi000328802900007
dc.contributor.authorscopusid6602218913-
dc.contributor.authorscopusid7006788384-
dc.contributor.authorscopusid7801474073-
dc.contributor.authorscopusid7005962555-
dc.description.lastpage102-
dc.identifier.issue1-
dc.description.firstpage83-
dc.relation.volume18-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.contributor.daisngid1202623
dc.contributor.daisngid237038
dc.contributor.daisngid3898650
dc.contributor.daisngid30319800
dc.contributor.wosstandardWOS:Krissian, K
dc.contributor.wosstandardWOS:Carreira, JM
dc.contributor.wosstandardWOS:Esclarin, J
dc.contributor.wosstandardWOS:Maynar, M
dc.date.coverdateEnero 2014
dc.identifier.ulpgces
dc.description.sjr1,505
dc.description.jcr3,654
dc.description.sjrqQ1
dc.description.jcrqQ1
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptAnálisis Matemático de Imágenes y Gráficos por Ordenador-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0003-1339-8700-
crisitem.author.parentorgDepartamento de Informática y Sistemas-
crisitem.author.fullNameKrissian , Karl-
crisitem.author.fullNameEsclarín Monreal, Julio-
Appears in Collections:Artículos
Show simple item record

SCOPUSTM   
Citations

13
checked on Jun 20, 2021

WEB OF SCIENCETM
Citations

9
checked on Jun 20, 2021

Page view(s)

42
checked on Jun 21, 2021

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.