کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6023361 | 1580874 | 2016 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
STGP: Spatio-temporal Gaussian process models for longitudinal neuroimaging data
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: STGP: Spatio-temporal Gaussian process models for longitudinal neuroimaging data STGP: Spatio-temporal Gaussian process models for longitudinal neuroimaging data](/preview/png/6023361.png)
چکیده انگلیسی
Longitudinal neuroimaging data plays an important role in mapping the neural developmental profile of major neuropsychiatric and neurodegenerative disorders and normal brain. The development of such developmental maps is critical for the prevention, diagnosis, and treatment of many brain-related diseases. The aim of this paper is to develop a spatio-temporal Gaussian process (STGP) framework to accurately delineate the developmental trajectories of brain structure and function, while achieving better prediction by explicitly incorporating the spatial and temporal features of longitudinal neuroimaging data. Our STGP integrates a functional principal component model (FPCA) and a partition parametric space-time covariance model to capture the medium-to-large and small-to-medium spatio-temporal dependence structures, respectively. We develop a three-stage efficient estimation procedure as well as a predictive method based on a kriging technique. Two key novelties of STGP are that it can efficiently use a small number of parameters to capture complex non-stationary and non-separable spatio-temporal dependence structures and that it can accurately predict spatio-temporal changes. We illustrate STGP using simulated data sets and two real data analyses including longitudinal positron emission tomography data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and longitudinal lateral ventricle surface data from a longitudinal study of early brain development.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 134, 1 July 2016, Pages 550-562
Journal: NeuroImage - Volume 134, 1 July 2016, Pages 550-562
نویسندگان
Jung Won Hyun, Yimei Li, Chao Huang, Martin Styner, Weili Lin, Hongtu Zhu, for the Alzheimer's Disease Neuroimaging Initiative for the Alzheimer's Disease Neuroimaging Initiative,