Paper
22 September 2015 Tutte polynomial in functional magnetic resonance imaging
Author Affiliations +
Abstract
Methods of graph theory are applied to the processing of functional magnetic resonance images. Specifically the Tutte polynomial is used to analyze such kind of images. Functional Magnetic Resonance Imaging provide us connectivity networks in the brain which are represented by graphs and the Tutte polynomial will be applied. The problem of computing the Tutte polynomial for a given graph is #P-hard even for planar graphs. For a practical application the maple packages “GraphTheory” and “SpecialGraphs” will be used. We will consider certain diagram which is depicting functional connectivity, specifically between frontal and posterior areas, in autism during an inferential text comprehension task. The Tutte polynomial for the resulting neural networks will be computed and some numerical invariants for such network will be obtained. Our results show that the Tutte polynomial is a powerful tool to analyze and characterize the networks obtained from functional magnetic resonance imaging.
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Marlly Verónica García-Castillón "Tutte polynomial in functional magnetic resonance imaging", Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 95992X (22 September 2015); https://doi.org/10.1117/12.2189788
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KEYWORDS
Neural networks

Functional magnetic resonance imaging

Data storage

Diffusion

Brain

Neuroimaging

Image enhancement

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