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Automated detection of depression from brain structural magnetic resonance imaging (sMRI) scans

Kipli, Kuryati 2014, Automated detection of depression from brain structural magnetic resonance imaging (sMRI) scans, PhD (Engineering) thesis, School of Engineering, Deakin University.

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Title Automated detection of depression from brain structural magnetic resonance imaging (sMRI) scans
Author Kipli, Kuryati
Institution Deakin University
School School of Engineering
Faculty Faculty of Science, Engineering and Built Environment
Degree type Research doctorate
Degree name PhD (Engineering)
Thesis advisor Kouzani, Abbas
Xiang, Yong
Joordens, Matthew
Date submitted 2014-11
Keyword(s) depression detection system
structural magnetic resonance imaging (sMRI) scans
brain
Summary  Automated sMRI-based depression detection system is developed whose components include acquisition and preprocessing, feature extraction, feature selection, and classification. The core focus of the research is on the establishment of a new feature selection algorithm that quantifies the most relevant brain volumetric feature for depression detection at an individual level.
Language eng
Field of Research 090399 Biomedical Engineering not elsewhere classified
080106 Image Processing
090609 Signal Processing
Socio Economic Objective 970109 Expanding Knowledge in Engineering
Description of original xvii, 143 pages : illustrations, tables, graphs
Dewey Decimal Classification 616.80475418
Restricted until 2017-02-16
Copyright notice ┬ęThe author
Free to Read? No
Free to Read Start Date 2016-09-23
Persistent URL http://hdl.handle.net/10536/DRO/DU:30074518

Document type: Thesis
Collection: Higher degree theses (citation only)
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Created: Thu, 16 Jul 2015, 16:24:52 EST by Kate Percival

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