Convolutional Neural Networks For Identification Of Axial 2d Slices In Ct Data

Simple item page
but.event.date26.04.2018cs
but.event.titleStudent EEICT 2018cs
dc.contributor.authorVavřinová, Pavlína
dc.date.accessioned2019-03-04T10:05:33Z
dc.date.available2019-03-04T10:05:33Z
dc.date.issued2018cs
dc.description.abstractThis thesis deals with the classification of 2D axial slices in CT patient’s data. The classification is realized into six categories. The sphere of convolutional neural networks was used for this purpose and AlexNet network was specifically selected for the intention of this identification, which was applied to the created data set after being adaptated. The overall classification success rate was 84%. In addition, an analysis of mistakes in classification was performed.en
dc.formattextcs
dc.format.extent21-23cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings of the 24th Conference STUDENT EEICT 2018. s. 21-23. ISBN 978-80-214-5614-3cs
dc.identifier.isbn978-80-214-5614-3
dc.identifier.urihttp://hdl.handle.net/11012/138156
dc.language.isoczcs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 24th Conference STUDENT EEICT 2018en
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 networksen
dc.subjectdeep learningen
dc.subjectconvolutional neural networksen
dc.subjectAlexNeten
dc.titleConvolutional Neural Networks For Identification Of Axial 2d Slices In Ct Dataen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
eeict2018-21.pdf
Size:
479.05 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Student EEICT 2018