Braph : a toolbox developed for brain graph analysis of various imaging modalities
buir.advisor | Volpe, Giovanni | |
dc.contributor.author | Kakaei, Ehsan | |
dc.date.accessioned | 2017-03-31T13:26:15Z | |
dc.date.available | 2017-03-31T13:26:15Z | |
dc.date.copyright | 2017-03 | |
dc.date.issued | 2017-03 | |
dc.date.submitted | 2017-03-21 | |
dc.description | Cataloged from PDF version of article. | en_US |
dc.description | Thesis (M.S.): Bilkent University, Department of Physics, İhsan Doğramacı Bilkent University, 2017. | en_US |
dc.description | Includes bibliographical references (leaves 41-45). | en_US |
dc.description.abstract | Complex systems, like the human brain, are composed of a huge number of interacting elements showing complex patterns. Graph theory provides a mathematical toolbox for investigating the role of each element in these systems. With the rise of interest in applying this method for studying brain networks, several software have been developed to allow researches conduct brain network analysis. However, a comprehensive and an easy-to-use toolbox is still lacking. BRAPH is the first object-oriented toolbox that provides users the ability of constructing and analyzing brain networks out of data acquired from various imaging modalities. For this purpose, multiple graphical user interfaces (GUIs) have been designed that allow the users to import or build brain atlases, along with cohort of subjects, prior to starting the graph analysis. Various graph measures for both weighted graphs and binary graphs, comparison between groups, comparison with random graphs, longitudinal analysis and statistical analysis, are only some of the analysis tools embedded in BRAPH. | en_US |
dc.description.provenance | Submitted by Betül Özen (ozen@bilkent.edu.tr) on 2017-03-31T13:26:15Z No. of bitstreams: 1 10143455.pdf: 4737795 bytes, checksum: 6227b68b9ad23b9a84e2f8e0479be885 (MD5) | en |
dc.description.provenance | Made available in DSpace on 2017-03-31T13:26:15Z (GMT). No. of bitstreams: 1 10143455.pdf: 4737795 bytes, checksum: 6227b68b9ad23b9a84e2f8e0479be885 (MD5) Previous issue date: 2017-03 | en |
dc.description.statementofresponsibility | by Ehsan Kakaei. | en_US |
dc.embargo.release | 2020-03-21 | |
dc.format.extent | x, 45 leaves : charts ; 29 cm. | en_US |
dc.identifier.itemid | B155349 | |
dc.identifier.uri | http://hdl.handle.net/11693/32939 | |
dc.language.iso | English | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Graph theory analysis | en_US |
dc.subject | Object-oriented software | en_US |
dc.subject | Network topology | en_US |
dc.subject | Longitudinal analysis | en_US |
dc.title | Braph : a toolbox developed for brain graph analysis of various imaging modalities | en_US |
dc.title.alternative | Bose-Einstein yoğuşmalarındaki karanlık solitonların kütlelerinin Gelfand Yaglom metodu ile hesaplanması | en_US |
dc.type | Thesis | en_US |
thesis.degree.discipline | Physics | |
thesis.degree.grantor | Bilkent University | |
thesis.degree.level | Master's | |
thesis.degree.name | MS (Master of Science) |