Detection Of Pathological Vertebrae In Spinal Ct Utilised By Machine Learning Methods

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but.event.date25.04.2019cs
but.event.titleStudent EEICT 2019cs
dc.contributor.authorTyshchenko, Bohdan
dc.date.accessioned2020-04-16T07:19:35Z
dc.date.available2020-04-16T07:19:35Z
dc.date.issued2019cs
dc.description.abstractThis paper presents a computer aided detection system to identify pathological vertebrae and to classify a type of pathology. Designed classification system is based on using neural network (NN), which performs classification step and on principal component analysis (PCA), which is used to reducing the original number of observation features.en
dc.formattextcs
dc.format.extent390-393cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings of the 25st Conference STUDENT EEICT 2019. s. 390-393. ISBN 978-80-214-5735-5cs
dc.identifier.isbn978-80-214-5735-5
dc.identifier.urihttp://hdl.handle.net/11012/186700
dc.language.isocscs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 25st Conference STUDENT EEICT 2019en
dc.relation.urihttp://www.feec.vutbr.cz/EEICT/cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectNeural networken
dc.subjectClassificationen
dc.subjectCTen
dc.subjectMachine Learningen
dc.subjectPathologies of spineen
dc.subjectPrincipal Component Analysisen
dc.subjectVertebraen
dc.titleDetection Of Pathological Vertebrae In Spinal Ct Utilised By Machine Learning Methodsen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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