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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1720
DC FieldValueLanguage
dc.contributor.authorLe Dinh Chuongen_US
dc.date.accessioned2023-10-26T04:09:52Z-
dc.date.available2023-10-26T04:09:52Z-
dc.date.issued2023-
dc.identifier.urihttps://epub.vgu.edu.vn/handle/dlibvgu/1720-
dc.description.abstractDuring the process of fMRI data analysing, it often takes a lot of time and effort to label the region of interest, which are the parts of the brain that activate when the host executes some task. In this work, a solution to this problem is proposed that utilizes a powerful and newly emerged technology: graph neural network. The solution is an end-to-end pipeline, from transforming the fMRI data into graph to classifying the data into five categories: noise, default mode network, primary vision, auditory, and motor. The pipeline shows a great performance on the two selected datasetsen_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectFMRIen_US
dc.subjectMachine learningen_US
dc.subjectGraph neutral networken_US
dc.subjectRegion of interesten_US
dc.subjectClassificationen_US
dc.titleGraph neutral network for fMRI region of interest classtificationen_US
dc.typeThesisen_US
item.grantfulltextrestricted-
item.fulltextWith Fulltext-
item.languageiso639-1other-
Appears in Collections:Computer Science (CS)
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