VGU RESEARCH REPOSITORY
Please use this identifier to cite or link to this item:
https://epub.vgu.edu.vn/handle/dlibvgu/1720| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Le Dinh Chuong | en_US |
| dc.date.accessioned | 2023-10-26T04:09:52Z | - |
| dc.date.available | 2023-10-26T04:09:52Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | https://epub.vgu.edu.vn/handle/dlibvgu/1720 | - |
| dc.description.abstract | During 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 datasets | en_US |
| dc.language.iso | en | en_US |
| dc.rights | Attribution-NonCommercial 4.0 International | * |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | * |
| dc.subject | FMRI | en_US |
| dc.subject | Machine learning | en_US |
| dc.subject | Graph neutral network | en_US |
| dc.subject | Region of interest | en_US |
| dc.subject | Classification | en_US |
| dc.title | Graph neutral network for fMRI region of interest classtification | en_US |
| dc.type | Thesis | en_US |
| item.grantfulltext | restricted | - |
| item.fulltext | With Fulltext | - |
| item.languageiso639-1 | other | - |
| Appears in Collections: | Computer Science (CS) | |
Files in This Item:
| File | Description | Size | Format | Existing users please Login |
|---|---|---|---|---|
| Graph neutral network for fMRI region of interest classtification.pdf | 2.95 MB | Adobe PDF |
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