Deep transformation method for discriminant analysis of multi-channel resting state fMRI
Date
2019
Authors
Aradhya, A.M.S.
Joglekar, A.
Suresh, S.
Pratama, M.
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Conference paper
Citation
Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence, 2019, vol.33, iss.01, pp.2556-2563
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AAAI-19 Thirty-Third AAAI Conference on Artificial Intelligence (27 Jan 2019 - 1 Feb 2019 : Hawaii, USA)
Abstract
Analysis of resting state - functional Magnetic Resonance Imaging (rs-fMRI) data has been a challenging problem due to a high homogeneity, large intra-class variability, limited samples and difference in acquisition technologies/techniques. These issues are predominant in the case of Attention Deficit Hyperactivity Disorder (ADHD). In this paper, we propose a new Deep Transformation Method (DTM) that extracts the discriminant latent feature space from rs-fMRI and projects it in the subsequent layer for classification of rs-fMRI data. The hidden transformation layer in DTM projects the original rs-fMRI data into a new space using the learning policy and extracts the spatio-temporal correlations of the functional activities as a latent feature space.
The subsequent convolution and decision layers transform the latent feature space into high-level features and provide accurate classification. The performance of DTM has been evaluated using the ADHD200 rs-fMRI benchmark data with cross-validation. The results show that the proposed DTM achieves a mean classification accuracy of 70.36% and an improvement of 8.25% on the state of the art methodologies was observed. The improvement is due to concurrent analysis of the spatio-temporal correlations between the different regions of the brain and can be easily extended to study other cognitive disorders using rs-fMRI. Further, brain network analysis has been studied to identify the difference in functional activities and the corresponding regions behind cognitive symptoms in ADHD.
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Link to a related website: https://openaccessbutton.org/?title=Deep+transformation+method+for+discriminant+analysis+of+multi-channel+resting+state+fMRI, Open Access via Unpaywall
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Copyright 2019, Association for the Advancement of Artificial Intelligence (http://www.aaai.org/)