Network analysis on neuro-imaging data
Neuroimaging is an effective technique to examine the structure and connectivity of human brains. Also, neuroimaging data has been widely used in clinical diagnosis and research areas. This project is to develop a method to predict the age group that the brain belongs to using neuroimaging data. Ne...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/148043 |
| _version_ | 1826122271614304256 |
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| author | Tang, Hexuan |
| author2 | Ke Yiping, Kelly |
| author_facet | Ke Yiping, Kelly Tang, Hexuan |
| author_sort | Tang, Hexuan |
| collection | NTU |
| description | Neuroimaging is an effective technique to examine the structure and connectivity of human brains. Also, neuroimaging data has been widely used in clinical diagnosis and research areas.
This project is to develop a method to predict the age group that the brain belongs to using neuroimaging data. Neuroimaging data were collected from public sources and processed using existing pipelines. Default mode brain network was constructed from processed neuroimaging data. Network analytics method was applied and several network features such as efficiency, clustering coefficient were selected and calculated. The calculated data was used for classifier training purposes. Three different multiclass classifiers, OneVsOne, OneVsRest, and K-NN classifiers were trained. Evaluation of performance was done on each trained classifier based on calculated accuracy and F1 score. This was to compare and find out the most suitable classification algorithm for brain age group classification and prediction. From the result obtained, the classifiers can have high accuracy and make accurate classification and prediction of the brain age group. |
| first_indexed | 2024-10-01T05:45:46Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/148043 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:45:46Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1480432021-04-22T06:35:19Z Network analysis on neuro-imaging data Tang, Hexuan Ke Yiping, Kelly School of Computer Science and Engineering ypke@ntu.edu.sg Engineering::Computer science and engineering Neuroimaging is an effective technique to examine the structure and connectivity of human brains. Also, neuroimaging data has been widely used in clinical diagnosis and research areas. This project is to develop a method to predict the age group that the brain belongs to using neuroimaging data. Neuroimaging data were collected from public sources and processed using existing pipelines. Default mode brain network was constructed from processed neuroimaging data. Network analytics method was applied and several network features such as efficiency, clustering coefficient were selected and calculated. The calculated data was used for classifier training purposes. Three different multiclass classifiers, OneVsOne, OneVsRest, and K-NN classifiers were trained. Evaluation of performance was done on each trained classifier based on calculated accuracy and F1 score. This was to compare and find out the most suitable classification algorithm for brain age group classification and prediction. From the result obtained, the classifiers can have high accuracy and make accurate classification and prediction of the brain age group. Bachelor of Engineering (Computer Science) 2021-04-22T06:35:19Z 2021-04-22T06:35:19Z 2021 Final Year Project (FYP) Tang, H. (2021). Network analysis on neuro-imaging data. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148043 https://hdl.handle.net/10356/148043 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering Tang, Hexuan Network analysis on neuro-imaging data |
| title | Network analysis on neuro-imaging data |
| title_full | Network analysis on neuro-imaging data |
| title_fullStr | Network analysis on neuro-imaging data |
| title_full_unstemmed | Network analysis on neuro-imaging data |
| title_short | Network analysis on neuro-imaging data |
| title_sort | network analysis on neuro imaging data |
| topic | Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/148043 |
| work_keys_str_mv | AT tanghexuan networkanalysisonneuroimagingdata |