کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6033497 1188747 2012 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Dynamic Bayesian network modeling for longitudinal brain morphometry
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
Dynamic Bayesian network modeling for longitudinal brain morphometry
چکیده انگلیسی
Identifying interactions among brain regions from structural magnetic-resonance images presents one of the major challenges in computational neuroanatomy. We propose a Bayesian data-mining approach to the detection of longitudinal morphological changes in the human brain. Our method uses a dynamic Bayesian network to represent evolving inter-regional dependencies. The major advantage of dynamic Bayesian network modeling is that it can represent complicated interactions among temporal processes. We validated our approach by analyzing a simulated atrophy study, and found that this approach requires only a small number of samples to detect the ground-truth temporal model. We further applied dynamic Bayesian network modeling to a longitudinal study of normal aging and mild cognitive impairment - the Baltimore Longitudinal Study of Aging. We found that interactions among regional volume-change rates for the mild cognitive impairment group are different from those for the normal-aging group.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 59, Issue 3, 1 February 2012, Pages 2330-2338
نویسندگان
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