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. Attached Files Name Description MIMEType Size Downloads Title Parameter estimation of the BOLD fMRI model within a general particle filter framework Author(s) Hettiarachchi, Imali T. orcid.org/0000-0002-4220-0970 Mohamed, Shady orcid.org/0000-0002-8851-1635 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 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 Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research   Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Fri, 24 May 2013, 12:08:18 EST Fri, 24 May 2013, 14:07:38 EST Mon, 27 May 2013, 16:52:53 EST Tue, 28 May 2013, 08:24:40 EST Fri, 06 Feb 2015, 11:10:49 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 140 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Fri, 24 May 2013, 12:08:18 EST