Abstract
Detection of active areas in a human brain by functional magnetic resonance imaging (fMRI) is a challenging problem in medical imaging. Moreover, determining the onset and end of activation signals can determine temporal relationships required for brain mapping. In this paper, a comparative study for detecting active areas in fMRI data using Bayesian and classical approaches was introduced. It has been found that using Bayesian model provides accurate and sensitive detection.
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Mohamed, M.A., Abou-Chadi, F., Ouda, B.K. (2007). Analysis of fMRI Data Using Classical and Bayesian Approaches: A Comparative Study. In: Magjarevic, R., Nagel, J.H. (eds) World Congress on Medical Physics and Biomedical Engineering 2006. IFMBE Proceedings, vol 14. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36841-0_221
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DOI: https://doi.org/10.1007/978-3-540-36841-0_221
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