Graphical models of brain functional connectivity have matured from con rming a priori hypotheses to an exploratory tool for discovering unknown connectivity. However, exploratory...
We propose an original approach for the segmentation of three-dimensional fields of probability density functions. This presents a wide range of applications in medical images proc...
We introduce a novel approach for magnetic resonance image (MRI) brain tissue classification by learning image neighborhood statistics from noisy input data using nonparametric den...
Tolga Tasdizen, Suyash P. Awate, Ross T. Whitaker,...
The perplexing effects of noise and high feature dimensionality greatly complicate functional magnetic resonance imaging (fMRI) classification. In this paper, we present a novel f...
ICA (independent component analysis) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such ...