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31 January 2020 FMRI image segmentation based on hidden Markov random field with directional statistics observation model
Oleg Lukashenko, S. D. Chernyaev
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Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114331D (2020) https://doi.org/10.1117/12.2559545
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands
Abstract
In this paper we consider the problem of segmentation of three-dimensional fMRI images within the Bayesian framework with Markov Random Field (MRF) as the prior distribution and von Mises-Fisher distribution as the likelihood. Usually, the learning of such models is a complicated task and the exact inference is impossible in practice. To fit the proposed model, we apply the mean field approximation on the inference step in the EM algorithm. Some numerical examples are presented to illustrate the proposed method.
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Oleg Lukashenko and S. D. Chernyaev "FMRI image segmentation based on hidden Markov random field with directional statistics observation model", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114331D (31 January 2020); https://doi.org/10.1117/12.2559545
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KEYWORDS
Image segmentation
Functional magnetic resonance imaging
Expectation maximization algorithms
Monte Carlo methods
Data modeling
Statistical modeling
Statistical analysis
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