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Automatic Denoising of Functional MRI Data: Combining Independent Component Analysis and Hierarchical Fusion of Classifiers
Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult. Independent component analysis (ICA) - one of the most widely used techniques for the exploratory analysis of fMRI data - has shown...
Tallennettuna:
| Päätekijät: | , , , , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
2014
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4019210/ https://ncbi.nlm.nih.gov/pubmed/24389422 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2013.11.046 |
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