Convex hull in brain tumor segmentation

Basit Öğe Kaydı
dc.authorid0000-0001-6657-9738
dc.contributor.authorSailunaz, Kashfia
dc.contributor.authorBeştepe, Deniz
dc.contributor.authorAlhajj, Sleiman
dc.contributor.authorÖzyer, Tansel
dc.contributor.authorRokne, Jon
dc.contributor.authorAlhajj, Reda
dc.date.accessioned2022-09-15T09:22:52Z
dc.date.available2022-09-15T09:22:52Z
dc.date.issued2022
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.departmentİstanbul Medipol Üniversitesi, Uluslararası Tıp Fakültesi
dc.description.abstractTumors are the second leading cause of death. Among the tumors, brain tumors constitute one of the most complex tumor categories with a high mortality rate. Therefore, brain tumor detection and segmentation from non-invasive imaging like MRI is an important research area. Although most recent researches for brain tumor detection are focused on deep learning methods, machine learning, geometrical approaches, thresholding and hybrid models are also explored frequently. In this paper, a novel brain tumor segmentation method containing thresholding, computational geometry and heuristics is proposed. The proposed model is tested with two brain tumor datasets to show comparative results for brain tumor segmentation with thresholding, convex hull and an area heuristic. The application of different filtering on a direct convex hull model and a heuristic-based convex hull model shows that the convex area based heuristic with the convex hull approach is able to segment brain tumors more accurately than previous approaches.
dc.identifier.citationSailunaz, K., Beştepe, D., Alhajj, S., Özyer, T., Rokne, J. ve Alhajj, R. (2022). Convex hull in brain tumor segmentation. 15th International Conference on Brain Informatics, BI 2022 içinde (210-225. ss.). Virtual, Online, 15-17 July 2022. https://doi.org/10.1007/978-3-031-15037-1_18
dc.identifier.doi10.1007/978-3-031-15037-1_18
dc.identifier.endpage225
dc.identifier.isbn9783031150364
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.scopus2-s2.0-85136950293
dc.identifier.scopusqualityN/A
dc.identifier.startpage210
dc.identifier.urihttps://doi.org/10.1007/978-3-031-15037-1_18
dc.identifier.urihttps://hdl.handle.net/20.500.12511/9709
dc.identifier.volume13406
dc.identifier.wos000878133000018en_US
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorBeştepe, Deniz
dc.institutionauthorAlhajj, Sleiman
dc.institutionauthorAlhajj, Reda
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartof15th International Conference on Brain Informatics, BI 2022en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBrain Tumor
dc.subjectConvex Hull
dc.subjectImage Analysis
dc.subjectSegmentation
dc.titleConvex hull in brain tumor segmentation
dc.typeConference Object

Dosyalar

Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Bildiri Koleksiyonu
Bildiri Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu