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Proceedings Paper

Joint source based analysis of multiple brain structures in studying major depressive disorder
Author(s): Mahdi Ramezani; Abtin Rasoulian; Tom Hollenstein; Kate Harkness; Ingrid Johnsrude; Purang Abolmaesumi
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Paper Abstract

We propose a joint Source-Based Analysis (jSBA) framework to identify brain structural variations in patients with Major Depressive Disorder (MDD). In this framework, features representing position, orientation and size (i.e. pose), shape, and local tissue composition are extracted. Subsequently, simultaneous analysis of these features within a joint analysis method is performed to generate the basis sources that show signi cant di erences between subjects with MDD and those in healthy control. Moreover, in a cross-validation leave- one-out experiment, we use a Fisher Linear Discriminant (FLD) classi er to identify individuals within the MDD group. Results show that we can classify the MDD subjects with an accuracy of 76% solely based on the information gathered from the joint analysis of pose, shape, and tissue composition in multiple brain structures.

Paper Details

Date Published: 21 March 2014
PDF: 6 pages
Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90341P (21 March 2014); doi: 10.1117/12.2042275
Show Author Affiliations
Mahdi Ramezani, The Univ. of British Columbia (Canada)
Abtin Rasoulian, The Univ. of British Columbia (Canada)
Tom Hollenstein, Queen's Univ. (Canada)
Kate Harkness, Queen's Univ. (Canada)
Ingrid Johnsrude, Queen's Univ. (Canada)
Purang Abolmaesumi, The Univ. of British Columbia (Canada)


Published in SPIE Proceedings Vol. 9034:
Medical Imaging 2014: Image Processing
Sebastien Ourselin; Martin A. Styner, Editor(s)

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