Chest X-ray Image Analysis using Convolutional Vision Transformer

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but.event.date25.04.2023cs
but.event.titleSTUDENT EEICT 2023cs
dc.contributor.authorMezina, Anzhelika
dc.contributor.authorBurget, Radim
dc.date.accessioned2023-07-17T05:57:34Z
dc.date.available2023-07-17T05:57:34Z
dc.date.issued2023cs
dc.description.abstractIn recent years, computer techniques for clinical imageanalysis have been improved significantly, especially becauseof the pandemic situation. Most recent approaches are focusedon the detection of viral pneumonia or COVID-19 diseases.However, there is less attention to common pulmonary diseases,such as fibrosis, infiltration and others. This paper introduces theneural network, which is aimed to detect 14 pulmonary diseases.This model is composed of two branches: global, which is theInceptionNetV3, and local, which consists of Inception modulesand a modified Vision Transformer. Additionally, the AsymmetricLoss function was utilized to deal with the problem of multilabelclassification. The proposed model has achieved an AUC of 0.8012and an accuracy of 0.7429, which outperforms the well-knownclassification models.en
dc.formattextcs
dc.format.extent161-165cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings II of the 29st Conference STUDENT EEICT 2023: Selected papers. s. 161-165. ISBN 978-80-214-6154-3cs
dc.identifier.doi10.13164/eeict.2023.161
dc.identifier.isbn978-80-214-6154-3
dc.identifier.issn2788-1334
dc.identifier.urihttp://hdl.handle.net/11012/210681
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings II of the 29st Conference STUDENT EEICT 2023: Selected papersen
dc.relation.urihttps://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdfcs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectdeep learningen
dc.subjectmultilabel classificationen
dc.subjectchest Xrayimagesen
dc.subjectVision transformeren
dc.subjectInceptionNetV3en
dc.titleChest X-ray Image Analysis using Convolutional Vision Transformeren
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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