Paper
21 March 2014 Joint source based analysis of multiple brain structures in studying major depressive disorder
Mahdi Ramezani, Abtin Rasoulian, Tom Hollenstein, Kate Harkness, Ingrid Johnsrude, Purang Abolmaesumi
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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.
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Mahdi Ramezani, Abtin Rasoulian, Tom Hollenstein, Kate Harkness, Ingrid Johnsrude, and Purang Abolmaesumi "Joint source based analysis of multiple brain structures in studying major depressive disorder", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90341P (21 March 2014); https://doi.org/10.1117/12.2042275
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Cited by 3 scholarly publications.
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KEYWORDS
Brain

Tissues

Magnetic resonance imaging

Shape analysis

Associative arrays

Brain mapping

Modulation

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