کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6036813 | 1188780 | 2009 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Smoothing dynamic positron emission tomography time courses using functional principal components
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب شناختی
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چکیده انگلیسی
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 nonparametric covariate adjustment, it is possible to smooth the PET time course data thus reducing the noise. A new model for functional data analysis, the Multiplicative Nonparametric Random Effects Model, is introduced to more accurately account for the variation in the data. A locally adaptive bandwidth choice helps to determine the correct amount of smoothing at each time point. This preprocessing step to smooth the data then allows subsequent analysis by methods such as Spectral Analysis to be substantially improved in terms of their mean squared error.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 47, Issue 1, 1 August 2009, Pages 184-193
Journal: NeuroImage - Volume 47, Issue 1, 1 August 2009, Pages 184-193
نویسندگان
Ci-Ren Jiang, John A.D. Aston, Jane-Ling Wang,