A fusion method for pulmonary nodule segmentation in chest CT image sets

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dc.authorid0000-0003-0490-5184
dc.authorwosidGuvenis, Albert/T-8866-2019
dc.authorwosidGuvenis, Albert/Q-2710-2015
dc.authorwosidTunali, Ilke/AAG-7120-2020
dc.contributor.authorTunalı, İlke
dc.contributor.authorGüveniş, Albert
dc.date.accessioned2022-05-11T14:16:02Z
dc.date.available2022-05-11T14:16:02Z
dc.date.issued2016
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Biyomedikal Mühendisliği Bölümü
dc.description3rd IEEE EMBS International Conference on Biomedical and Health Informatics (IEEE BHI) -- FEB 24-27, 2016 -- Las Vegas, NV
dc.description.abstractThis paper presents a fusion algorithm combining two methods for pulmonary nodule segmentation in Chest CT scans. Segmentation is an important task for both diagnosis and therapy monitoring. Since manual segmentation of volumes is time-consuming and there is an inter-observer variability between each radiologist, there have been numerous studies on developing schemes for automated segmentation of lung nodules. In order to segment nodules automatically, we have merged two proposed methods from the literature. First, a semi-automated segmentation method is used to find an initial estimate of the nodule using a non-fixed thresholding scheme. Then, the vessels and tissues connected to the nodule segment are removed by using a refinement method based on geodesic distances. The initial results indicate a 0.618 Jaccard index on 50% consensus ground truth data extracted from 18 non-solid and solid nodules from the LIDC-IDRI database, representing a significant improvement for this type of nodules. It is shown that fusion improves the segmentation process by combining the well performing parts of individual algorithms. We expect to further improve the results by fusing other algorithms.
dc.description.sponsorshipIEEE EMBS, IEEE, Journal of Biomed & Hlth Informat, IEEE Commun Soc
dc.identifier.endpage183
dc.identifier.isbn978-1-5090-2455-1
dc.identifier.scopus2-s2.0-84968638756
dc.identifier.startpage180
dc.identifier.urihttps://hdl.handle.net/20.500.11776/6156
dc.identifier.wosWOS:000381398000045
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorTunalı, İlke
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2016 3rd Ieee Embs International Conference on Biomedical and Health Informatics
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectSmall Lung Nodules
dc.subjectDatabase Consortium
dc.subjectScans
dc.titleA fusion method for pulmonary nodule segmentation in chest CT image sets
dc.typeConference Object

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