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Accurate registration plays a critical role in group-wise functional Magnetic Resonance Imaging (fMRI) image analysis, as spatial correspondence among different brain images is a prerequisite for inferring meaningful patterns. However, the problem is challenging and remains open, and more effort should be made to advance the state-of-the-art image registration methods for fMRI images. Inspired by...
With the growing number of audio excerpts through various media and distribution channels, advanced audio analysis approaches have received significant interest in the multimedia field. However, current audio analysis approaches are still far from satisfactory due to the semantic gaps between the low-level acoustic features and high-level semantics perceived by human brain. In order to alleviate the...
Segregation and integration are two general principles of the brain's functional architecture; therefore brain network analysis is of significant importance in understanding brain function. Critical to brain network analysis and construction is the identification of reliable, reproducible and accurate network nodes, or Regions of Interest (ROIs). In this paper, based on functional ROIs derived from...
In vivo parcellation of the cerebral cortex via non-invasive neuroimaging techniques has been in active research for over a decade. A variety of model-driven or data-driven computational approaches have been proposed to parcellate the cortex. A fundamental issue in these parcellation methodologies is the features or attributes used to define boundaries between cortical regions. This paper proposes...
Quantitative descriptions of white matter (WM) fiber shape and cortical folding patterns are important for neuroscience research. This paper presents a novel computational method for WM fiber shape pattern analysis, that is, WM fibers are clustered into five primitive shape patterns: closed `U', `M', curved line, open `U' and straight line, based on the automatic clustering of their shape features...
It is widely believed that the structural connectivity of a brain region largely determines its function. High resolution Diffusion Tensor Imaging (DTI) is now able to image the axonal fibers in vivo and the DTI tractography result provides rich connectivity information. In this paper, a novel method is proposed to employ fiber density information for automatic cortical parcellation based on the premise...
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