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Parameter estimation of the BOLD fMRI model within a general particle filter framework

Hettiarachchi, Imali T., Mohamed, Shady and Nahavandi, Saeid 2012, Parameter estimation of the BOLD fMRI model within a general particle filter framework, in ISMRM 2012 : Adapting MR in a Changing World : Proceedings of the 20th International Society for Magnetic Resonance in Medicine Annual Meeting and Exhibition, IEEE Compter Society, Piscataway, N.J., pp. 1-2.

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Title Parameter estimation of the BOLD fMRI model within a general particle filter framework
Author(s) Hettiarachchi, Imali T.ORCID iD for Hettiarachchi, Imali T. orcid.org/0000-0002-4220-0970
Mohamed, ShadyORCID iD for Mohamed, Shady orcid.org/0000-0002-8851-1635
Nahavandi, Saeid
Conference name International Society for Magnetic Resonance in Medicine. Meeting and Exhibition (20th : 2012 : Melbourne, Victoria)
Conference location Melbourne, Victoria
Conference dates 5-11 May. 2012
Title of proceedings ISMRM 2012 : Adapting MR in a Changing World : Proceedings of the 20th International Society for Magnetic Resonance in Medicine Annual Meeting and Exhibition
Editor(s) [Unknown]
Publication date 2012
Conference series International Society for Magnetic Resonance in Medicine Annual Meeting and Exhibition
Start page 1
End page 2
Total pages 2
Publisher IEEE Compter Society
Place of publication Piscataway, N.J.
Summary This work demonstrates a novel Bayesian learning approach for model based analysis of Functional Magnetic Resonance (fMRI) data. We use a physiologically inspired hemodynamic model and investigate a method to simultaneously infer the neural activity together with hidden state and the physiological parameter of the model. This joint estimation problem is still an open topic. In our work we use a Particle Filter accompanied with a kernel smoothing approach to address this problem within a general filtering framework. Simulation results show that the proposed method is a consistent approach and has a good potential to be enhanced for further fMRI data analysis.
Language eng
Field of Research 090399 Biomedical Engineering not elsewhere classified
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E2 Full written paper - non-refereed / Abstract reviewed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30052632

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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