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dc.contributor.authorÖzkan, Haydaren_US
dc.contributor.authorTulum, Gökalpen_US
dc.contributor.authorOsman, Onuren_US
dc.contributor.authorŞahin, Sinanen_US
dc.date.accessioned2019-07-22T11:23:08Z
dc.date.available2019-07-22T11:23:08Z
dc.date.issued2017en_US
dc.identifier.citationOzkan, H., Tulum, G., Osman, O., & Sahin, S. (2017). Automatic Detection of Pulmonary Embolism in CTA Images Using Machine Learning. Elektronika Ir Elektrotechnika, 23(1), 63-67. doi:10.5755/j01.eie.23.1.17585en_US
dc.identifier.issn1392-1215
dc.identifier.urihttps://hdl.handle.net/20.500.12294/1571
dc.descriptionOsman, Onur (Arel Author)en_US
dc.description.abstractIn this study, a novel computer-aided detection (CAD) method is introduced to detect pulmonary embolism (PE) in computed tomography angiography (CTA) images. This method consists of lung vessel segmentation, PE candidate detection, feature extraction, feature selection and classification of PE. PE candidates are determined in lung vessel tree. Then, feature extraction is carried out based on morphological properties of PEs. Stepwise feature selection method is used to find the best set of the features. Artificial neural network (ANN), k-nearest neighbours (KNN) and support vector machines (SVM) are used as classifiers. The CAD system is evaluated for 33 CTA datasets with 10 fold cross-validation. The sensitivities of these classifiers are obtained as 98.3 %, 57.3 % and 73 % at 10.2, 5.7 and 8.2 false positives per dataset respectively.en_US
dc.language.isoengen_US
dc.publisherKaunas Univ. Technologyen_US
dc.relation.ispartofElektronika Ir Elektrotechnikaen_US
dc.identifier.doi10.5755/j01.eie.23.1.17585en_US
dc.identifier.doi10.5755/j01.eie.23.1.17585
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial Neural Networken_US
dc.subjectK-Nearest Neighboursen_US
dc.subjectPulmonary Embolismen_US
dc.subjectSupport Vector Machinesen_US
dc.titleAutomatic Detection of Pulmonary Embolism in CTA Images Using Machine Learningen_US
dc.typearticleen_US
dc.departmentMühendislik ve Mimarlık Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.authorid0000-0001-7675-7999en_US
dc.identifier.volume23en_US
dc.identifier.issue1en_US
dc.identifier.startpage63en_US
dc.identifier.endpage67en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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