2026-09-19T16:07:52Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/82097 2023-07-11 col_2142_5131 col_2142_11614 com_2142_5130 com_2142_11613 com_2142_8903

Lawrence Hubert Shinkareva, Svetlana V. 2015-09-25T20:39:10Z 2015-09-25T20:39:10Z 10000-01-01 2005 2005 This dissertation considers the problem of classifying subjects into predefined groups based on functional magnetic resonance imaging (fMRI) data. Classification of subjects into predefined groups, such as patient vs. control, based on their functional MRI data is a potentially useful procedure for ensuring homogeneous research samples and for clinical diagnostic purposes. Unlike other methods addressing the same question that are using either predefined regions of interest or statistical parametric maps, the proposed methodology uses preprocessed time series for the whole brain volume. Using a training set of two groups of subjects the presented methodology identifies spatio-temporal features that distinguish the groups and uses these features to categorize new subjects. The methodology is illustrated using simulations and in vivo data sets. Made available in DSpace on 2015-09-25T20:39:10Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3199141.pdf: 2234691 bytes, checksum: dff79ac9a7d97df641fac8a25b12d004 (MD5) Previous issue date: 2005 Embargo set by: Seth Robbins for item 83378 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 83 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005. http://hdl.handle.net/2142/82097 (MiAaPQ)AAI3199141 eng Biology, Neuroscience A Model-Free Approach for Classification of fMRI Brain Images text Psychology Psychology University of Illinois at Urbana-Champaign Dissertation Ph.D.