Segmentation of fetal skulls using ellipse fitting and active appearance models

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dc.authorscopusid8372387400
dc.authorscopusid6603953162
dc.authorscopusid6603020540
dc.contributor.authorKonur U.
dc.contributor.authorGürgen F.
dc.contributor.authorVarol F.
dc.date.accessioned2024-06-12T10:25:24Z
dc.date.available2024-06-12T10:25:24Z
dc.date.issued2012
dc.description2012 20th Signal Processing and Communications Applications Conference, SIU 2012 -- 18 April 2012 through 20 April 2012 -- Fethiye, Mugla -- 90786en_US
dc.description.abstractIn this study, we use ultrasound (US) imaging modality frequently employed in prenatal diagnosis and axial skull images used primarily in the examination of fetal neural tubes and work on the segmentation of skull (and brain) structures. The segmentation performance of the mentioned structures is vital in that, applications such as automatic diagnosis systems can provide better feature extraction and classification performance with the aid of such a preprocessing. Our approach works with the principles of coarsely localizing the skull and brain structures present in US images acquired in transverse sections of fetal skulls using model (ellipse) fitting and successively obtaining more accurate segmentation with Active Appearance Models, which is a learning-based segmentation algorithm. © 2012 IEEE.en_US
dc.identifier.doi10.1109/SIU.2012.6204833
dc.identifier.isbn9.78147E+12
dc.identifier.scopus2-s2.0-84863494871en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/SIU.2012.6204833
dc.identifier.urihttps://hdl.handle.net/20.500.14551/16331
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.relation.ispartof2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectActive Appearance Models; Automatic Diagnosis; Brain Structure; Ellipse Fitting; Feature Extraction And Classification; Learning-Based Segmentation; Prenatal Diagnosis; Segmentation Performance; Transverse Section; Ultrasound Imaging; Diagnosis; Feature Extraction; Signal Processing; Image Segmentationen_US
dc.titleSegmentation of fetal skulls using ellipse fitting and active appearance modelsen_US
dc.title.alternativeEli?ps oturtma ve akti?f görünüm modelleri? kullanarak fetal kafatasi i?mgeleri?ni? bölütlemeen_US
dc.typeConference Objecten_US

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