Image processing algorithms for medical applications
Last few years has witnessed exponential growth in neuro-scientific field, especially for brain connectivity. Brain connectivity is primarily classified into three - structural connectivity, functional connectivity and effective connectivity. The advancement of neuroimaging techniques like fMRI has...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/10356/62074 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Last few years has witnessed exponential growth in neuro-scientific field, especially for brain connectivity. Brain connectivity is primarily classified into three - structural connectivity, functional connectivity and effective connectivity. The advancement of neuroimaging techniques like fMRI has accelerated the research pace. Among them, resting state fMRI has been gaining more momentum. Several observation and default mode network in the ‘task absent’ has caught the attention of scientists.
As for analysis, time series extraction and graphical model representation methods are the most popular. Time series extraction gives a platform to apply different mathematical algorithms that have also been in use in other fields. Same time graphical representation summaries the global and regional variance into biologically meaningful properties.
In this Final Year Project, a study on Functional connectivity analysis and Effective connectivity analysis were carried out. From the functional connectivity analyses, it has been observed that resting state connectivity of the brain is forming a Default Mode Network. |
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