The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
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...
We present an algorithmic pipeline to assess the dynamics on human brain networks based on multimodal resting state functional magnetic resonance imaging (rsfMRI) and diffusion tensor imaging (DTI) data. We employ white matter fiber density information to parcellate the cerebral cortex into functionally homogenous regions, which are used as nodes to construct functional brain networks. Then, the dynamics...
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...
Structural and functional brain connectivity has been extensively studied via diffusion tensor imaging (DTI) and functional MRI (fMRI) in recent years. An important aspect that has not been adequately addressed before is the connectivity state change in structurally-connected brain regions. In this paper, we present an intuitive approach that extracts feature vectors describing the functional connectivity...
Resting state fMRI (rsfMRI) has been demonstrated to be an effective modality by which to explore the functional networks of the human brain, as the low-frequency oscillations in rsfMRI time courses between spatially distant brain regions show the evidence of correlated activity patterns in the brain. This paper proposes a novel surface-based data-driven framework to explore these networks through...
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...
Cortical folding is an essential geometric characteristic of the human cerebral cortex. The cortical folding pattern conveys important information about brain architecture and function. Cortical thickness is another important morphological feature that reflects the size, density, and arrangement of cells in the cortex. Meanwhile, cortical regions are connected by short-distance or long-distance white...
The human brain anatomy is extremely variable across individuals in terms of its size, shape, and structure patterning. In this paper, a novel method is proposed for grouping brain MR images into different patterns. This method adopts the affinity propagation methodology to partition a population of brain images into different clusters. In the affinity propagation method, the tissue-segmented and...
Registration of DTI data with structure data, such as SPGR data, has import application in quantitative analysis of brain microstructures such as tissue diffusivity. However, due to potential problems such as EPI geometric distortion, partial volume effect and image reslicing errors, accurate registration of these two types of MRI images is challenging. In this paper, we present a novel deformable...
Reconstruction of the geometric central surface of the human cerebral cortex is an important means to study the structure and function of the brain cortex. In this paper, we propose a novel method based on an elastic deformable transform vector field to drive a deformable model for the reconstruction of the central surface of the brain cortex. In addition, simulated brain cortexes are generated to...
Mapping the cortical surface into a canonical coordinate space is an important means to study the structure and functional of the brain. Levy et al. (2002) proposed a least square conformal maps method by representing conformal energy as the square sense of the Cauchy-Riemann equation. It obtains good results in both angular distortion and computation time, although it introduces certain metric and...
We present a method for tissue classification based on diffusion-weighted imaging (DWI)/diffusion tensor imaging (DTI) data. Our motivation is that independent tissue segmentation based on DWI/DTI images provides complementary information to the tissue segmentation result using structural MRI data alone. The basis idea is to classify the brain into two compartments by utilizing the tissue contrast...
This paper proposes a novel method to define deformation invariant attribute vector for each voxel in 3D image for the purpose of anatomic correspondence detection. This is the extension of the work for 2D deformation invariant attribute using geodesic intensity histogram (GIH). Our original contribution is to extend this 2D technique to 3D image, and validate the method using synthesized deformation...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.