BibSonomy publications for /author/ZHANG/DiffusionTue Apr 22 10:36:30 CEST 2008Physica A: Statistical Mechanics and its ApplicationsFeb4764--772Fractional nonlinear diffusion equation and first passage time3872008Anomalous diffusion 01Mon Jan 21 10:54:26 CET 2008Communications of the ACM : CACMa publ. of the Association for Computing Machinery1235--39Implicit Structure and the Dynamics of BlogspaceVolume 47blogosphere diffusion Weblogs link together in a complex structure through which new ideas and discourse can flow. Such a structure is ideal for the study of the propagation of information. In this paper we describe general categories of information epidemics and create a tool to infer and visualize the paths specific infections take through the network. This inference is based in part on a novel utilization of data describing historical, repeating patterns of infection. We conclude with a description of a new ranking algorithm, iRank, for blogs. In contrast to traditional ranking strategies, iRank acts on the implicit link structure to find those blogs that initiate these epidemics. Workshop on the Weblogging Ecosystem, 13th International World Wide Web Conference, May 18th, 2004. Pre--print available as PDF (465Kb)Wed Jan 10 11:43:56 CET 2007Los Alamitos, CA, USAConference on Computer Vision and Pattern Recognition - CVPR'04588-593Estimation, Smoothing, and Characterization of Apparent Diffusion Coefficient Profiles from High Angular Resolution DWI012004Diffusion, Tensor DTI Imaging, Diffusion Wed Jan 10 11:43:56 CET 2007Proceedings ISMRM Workshop in Diffusion MRI: Biophysical IssuesMarch237--238Visualizing the Differences between Diffusion Tensor Volume Images2002Diffusion, Tensor DTI Imaging, Diffusion Wed Jan 10 11:43:56 CET 2007Medical Imaging, IEEE Transactions onSept.91127--1137White matter fiber tractography via anisotropic diffusion simulation in the human brain242005Diffusion, Tensor DTI Imaging, Diffusion A novel approach to noninvasively tracing brain white matter fiber tracts is presented using diffusion tensor magnetic resonance imaging (DT-MRI). This technique is based on successive anisotropic diffusion simulations over the human brain, which are utilized to construct three dimensional diffusion fronts. The fiber pathways are determined by evaluating the distance and orientation from the fronts to their corresponding diffusion seeds. Synthetic and real DT-MRI data are employed to demonstrate the tracking scheme. It is shown that the synthetic tracts are accurately replicated, and several major white matter fiber pathways can be reproduced noninvasively, with the tract branching being allowed. Since simulating the diffusion process, which is truly a physical phenomenon reflecting the underlying architecture of cerebral tissues, makes full use of the diffusion tensor data, including both the magnitude and orientation information, the proposed approach is expected to enhance robustness and reliability in white matter fiber reconstruction.Wed Jan 10 11:43:56 CET 2007Proceedings of the Scientific Meeting and Exhibition of the International Society for Magnetic Resonance in MedicineRamifications of Isotropic Sampling and Acquisition Orientation on {DTI} Analyses2004Diffusion, Tensor DTI Imaging, Diffusion Wed Jan 10 11:43:56 CET 2007Los Alamitos, CA, USAcvprw87Efficient Generation of Shape-Based Reference Frames for the Corpus Callosum for DTI-based Connectivity Analysis02006Diffusion, Tensor DTI Imaging, Diffusion Wed Jan 10 11:43:56 CET 2007Visualization and Image Processing of Tensor FieldsIn Press121--153An Introduction to Visualization of Diffusion Tensor Imaging and its Applications2005Diffusion, Tensor DTI Imaging, Diffusion Water dffusion is anisotropic in organized tissues such as white matter and muscle. Diffusion tensor imaging (DTI), a non-invasive MR technique, measures water self-diffusion rates and thus gives an indication of the underlying microstructure of tissue. The diffusion rate is often expressed by a second-order tensor. Visualizing DTI in an insightful way is challenging because of the high dimensionality of the diffusion tensor and the complex spatial relationships in a diffusion tensor field. This chapter surveys the different visualization techniques that have been developed for DTI and compares their main characteristics and drawbacks. We also discuss some of the many biomedical applications in which DTI helps extend our understanding or improve clinical procedures. We conclude with an overview of open problems and research directions.Wed Jan 10 11:43:56 CET 2007Los Alamitos, CA, USAConference on Computer Vision and Pattern Recognition - CVPR'04842-847Registration of Diffusion Tensor Images012004Diffusion, Tensor DTI Imaging, Diffusion Wed Jan 10 11:43:56 CET 2007Magnetic Resonance in Medicine1140--147Visualization and Analysis of White Matter Structural Asymmetry in Diffusion Tensor {MR} Imaging Data512004Diffusion, Tensor DTI Imaging, Diffusion Wed Jan 10 11:43:56 CET 2007Visualization '00 Work in ProgressOctoberStreamtubes and Streamsurfaces for Visualizing Diffusion Tensor {MRI} Volume Images2000Diffusion, Tensor Streamtube, Streamsurface DTI, Imaging, Diffusion Wed Jan 10 11:43:56 CET 2007Poster at Human Brain Project Annual Meeting, NIH, Bethesda, MDMayVisualizing Diffusion Tensor {MR} Images Using Streamtubes and Streamsurfaces2000Diffusion, Tensor DTI Imaging, Diffusion Wed Jan 10 11:43:56 CET 2007Visualization HandbookJuneDiffusion Tensor {MRI} Visualization2004Diffusion, Tensor DTI Imaging, Diffusion Wed Jan 10 11:43:56 CET 2007Washington, DC, USAVIS '04: Proceedings of the conference on Visualization '04598.29Visualization of the Interaction of Multiple Sclerosis Lesions with Adjacent White Matter Fibers Using Streamtubes and Streamsurfaces2004Diffusion, Tensor DTI Imaging, Diffusion Wed Jan 10 11:43:56 CET 2007IEEE Visualization Poster CompendiumOctoberApplication of {DTI} Visualization and Analysis on a Data Set from a Brain Tumor Patient2002Diffusion, Tensor DTI Imaging, Diffusion