Brain networks have a modular structure in function and this modular organization changes dynamically with time. However, the available brain network modularization methods are limited to detect functional modules for static brain network.So the aim of this sttudy is to propose a consensus algorithm to evaluate the modularization of functional brain network of healthy individuals and patients with Alzheimer's disease.The measures for the modularization of functional brain networks included normalized mutual information (NMI), average participation coefficient and classification accuracy.To evaluate the results from the consensus algorithm, machine learning based classification was performed on a new AD data sets.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords