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DC Field | Value | Language |
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dc.contributor.author | Garg, Gaurav | - |
dc.contributor.author | Prasad, Girijesh | - |
dc.contributor.author | Garg, Lalit | - |
dc.contributor.author | Coyle, Damien | - |
dc.date.accessioned | 2017-12-12T09:57:18Z | - |
dc.date.available | 2017-12-12T09:57:18Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | Garg, G., Prasad, G., Garg, L., & Coyle, D. (2011). Gaussian mixture models for brain activation detection from fmri data. International Journal of Bioelectromagnetism, 13(4), 255-260. | en_GB |
dc.identifier.issn | 14567865 | - |
dc.identifier.issn | 14567857 | - |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/24544 | - |
dc.description.abstract | Gaussian Mixture Model (GMM) based clustering has been successfully used in various types of medical and image data analysis, because of its robustness and stability under high noise levels. GMMs are employed in this work to extract the activation patterns from functional Magnetic Resonance Imaging (fMRI) data. The highly correlated time-series obtained with a given stimulus has been used to find the voxels contributing to the Blood Oxygenation Level Dependent (BOLD) activation regions. GMM clustering has been used for modeling of various activation patterns considering the strength, delay and duration of the epochs. A synthetic dataset and a real dataset provided by the Wellcome Trust Centre for Neuroimaging, University College London, UK are used to demonstrate the superiority of this approach in automating the process of identifying activated brain regions. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | International Society for Bioelectromagnetism | en_GB |
dc.rights | info:eu-repo/semantics/openAccess | en_GB |
dc.subject | Magnetic resonance imaging | en_GB |
dc.subject | Speech processing systems | en_GB |
dc.subject | Random noise theory | en_GB |
dc.subject | Ambient sounds | en_GB |
dc.title | Gaussian mixture models for brain activation detection from fmri data | en_GB |
dc.type | article | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
dc.publication.title | International Journal of Bioelectromagnetism | en_GB |
Appears in Collections: | Scholarly Works - FacICTCIS |
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Gaussian_Mixture_Models_for_Brain_Activation_Detec.pdf | 798.45 kB | Adobe PDF | View/Open |
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