Multiple-subjects connectivity-based parcellation using hierarchical Dirichlet process mixture models.
We propose a hierarchical infinite mixture model approach to address two issues in connectivity-based parcellations: (i) choosing the number of clusters, and (ii) combining data from different subjects. In a Bayesian setting, we model voxel-wise anatomical connectivity profiles as an infinite mixtur...
المؤلفون الرئيسيون: | Jbabdi, S, Woolrich, M, Behrens, T |
---|---|
التنسيق: | Journal article |
اللغة: | English |
منشور في: |
2009
|
مواد مشابهة
-
Tractography segmentation using a hierarchical Dirichlet processes mixture model
حسب: Wang, Xiaogang, وآخرون
منشور في: (2020) -
Spatially constrained hierarchical parcellation of the brain with resting-state fMRI.
حسب: Blumensath, T, وآخرون
منشور في: (2013) -
Dynamic classification of fetal heart rates by hierarchical Dirichlet process mixture models.
حسب: Kezi Yu, وآخرون
منشور في: (2017-01-01) -
Hierarchical Dirichlet processes
حسب: Teh, Y, وآخرون
منشور في: (2006) -
Hierarchical Dirichlet Process Based Gamma Mixture Modeling for Terahertz Band Wireless Communication Channels
حسب: Erhan Karakoca, وآخرون
منشور في: (2022-01-01)