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Smoothing Dynamic Positron Emission Tomography Time Courses Using Functional Principal Components
A functional smoothing approach to the analysis of PET time course data is presented. By borrowing information across space and accounting for this pooling through the use of a non-parametric covariate adjustment, it is possible to smooth the PET time course data thus reducing the noise. A new model...
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| Autors principals: | , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2009
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2715874/ https://ncbi.nlm.nih.gov/pubmed/19344774 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2009.03.051 |
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