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共 162 条记录，以下是151-160 订阅

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Interactive particle visualization with advanced shading models using lazy evaluation

Interactive particle visualization with advanced shading mod...

引用

7th Eurographics Symposium on Parallel Graphics and visualization, EGPGV 2007

作者： Gribble, Christiaan P. Parker, Steven G. Visual Simulation Group Department of Computer Science Grove City College Scientific Computing and Imaging Institute School of Computing University of Utah United States

ISBN: (纸本)9783905673500

Particle-based simulation methods are used to model a wide range of complex phenomena and to solve time-dependent problems of various scales. Effective visualizations of the resulting state will communicate subtle changes in the three-dimensional structure, spatial organization, and qualitative trends within a simulation as it evolves. We describe a visualization process targeting upcoming, highly parallel multicore desktop systems that enables interactive navigation and exploration of large particle datasets rendered with illumination effects from advanced shading models. These expensive illumination effects are evaluated lazily by decoupling interactive display and high quality rendering. We explore the performance characteristics of this approach and demonstrate its effectiveness using several large particle datasets. © The Eurographics Association 2007.

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Subdivision Volume Splatting

Subdivision Volume Splatting

引用

9th Joint Eurographics/IEEE VGTC Symposium on visualization, EuroVis 2007

作者： McDonnell, K.T. Neophytou, Neophytos Mueller, Klaus Qin, Hong Department of Mathematics and Computer Science Dowling College NY United States Center for Visual Computing Stony Brook University Stony BrookNY United States

ISBN: (纸本)9783905673456

Volumetric Subdivision (VS) is a powerful paradigm that enables volumetric sculpting and realistic volume deformations that give rise to the concept of "virtual clay". In VS, volumes are commonly represented as a space-filling set of deformed polyhedra, which can be further decomposed into a mesh of tetrahedra for rendering. Images can then be generated via tetrahedral projection or raycasting. A current shortcoming in VS-based operations is the need for a very high level of subdivision to represent fine detail in the mesh and to obtain a high-fidelity visualization. However, we have discovered that the subdivision process itself can be closely simulated with radial basis functions (RBFs), making it possible to replace the finer subdivision levels by a coarser aggregation of RBF kernels. This reduction to a simplified assembly of RBFs subsequently enables interactive rendering of volumetric subdivision shapes within a GPU-based volume splatting framework. © The Eurographics Association 2007.

关键词： Radial basis function networks

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GPU-Accelerated Volume Splatting with Elliptical RBFs

GPU-Accelerated Volume Splatting with Elliptical RBFs

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8th Joint Eurographics/IEEE VGTC Symposium on visualization, EuroVis 2006

作者： Neophytou, Neophytos Mueller, Klaus McDonnell, Kevin T. Hong, Wei Guan, Xin Qin, Hong Kaufman, Arie Center for Visual Computing Computer Science Stony Brook University United States Department of Mathematics and Computer Science Dowling College United States

ISBN: (纸本)3905673312

Radial Basis Functions (RBFs) have become a popular rendering primitive, both in surface and in volume rendering. This paper focuses on volume visualization, giving rise to 3D kernels. RBFs are especially convenient for the representation of scattered and irregularly distributed point samples, where the RBF kernel is used as a blending function for the space in between samples. Common representations employ radially symmetric RBFs, and various techniques have been introduced to render these, also with efficient implementations on programmable graphics hardware (GPUs). In this paper, we extend the existing work to more generalized, ellipsoidal RBF kernels, for the rendering of scattered volume data. We devise a post-shaded kernel-centric rendering approach, specifically designed to run efficiently on GPUs, and we demonstrate our renderer using datasets from subdivision volumes and computational science. © The Eurographics Association 2006.

关键词： Volume rendering

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Adaptive Frames-Based Denoising of Confocal Microscopy Data

Adaptive Frames-Based Denoising of Confocal Microscopy Data

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： A. Santamaria-Pang T.S. Bildea I. Konstantinidis I.A. Kakadiaris Computational Biomedicine Lab (formerly known as Visual Computing Lab) Department of Computer Science University of Houston TX USA The Norbert Wiener Center for Harmonic Analysis and Applications Department of Mathematics University of Maryland College Park MD USA

In this paper, we present a novel frames-based denoising algorithm. Using a general result on lifting frames, we construct a non-separable 3D frame capable of robust edge detection. This frame detects edge information by ensemble thresholding of the filtered data. The denoising uses a hysteresis thresholding step and an affine thresholding function, which are filter-adaptive and take full advantage of the threshold bounds. The threshold bounds are statistically determined from the given data for each directional filter. We compare our denoising method with other methods based on separable 3D wavelets and 3D median filtering, and report very encouraging results on applications to both synthetic and real confocal microscopy data

关键词： Noise reduction Microscopy Image edge detection Filter bank Additive noise Neurons Image reconstruction Biomedical computing Robustness Information filtering

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visual simulation of chemical gardens

Visual simulation of chemical gardens

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computer Graphics International Conference (CGI 2005)

作者： Wei, XM Qiu, F Li, W Yoakum-Stover, S Kaufman, A Computer Science Department Iona College United States Center for Visual Computing Department of Computer Science Stony Brook University United States Siemens Corporate Research United States

ISBN: (纸本)0780393309

We present a visualization and modeling system for the creation of chemical gardens. A chemical garden is a collection of plant-like structures formed when placing a soluble metal salt in an aqueous solution of sodium silicate. An accurate simulation of the chemical reaction of the metal salt and the physical behavior of the surrounding sodium silicate solution flow are complicated and time-consuming. Instead, in our system we use and propose a simplified 3D cellular automata (CA) approach to model the growing process of a chemical garden and its interaction with the solution flow. The input of our system is the shape and types of various soluble metal salts. Our program supports the visualization of the growth and formation of the chemical garden. The interactive rendering result on a texture mapping hardware also helps the user in observing and creating a desirable chemical garden.

关键词： cellular automata natural phenomena Modeling growing rules volume rendering

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visual simulation of chemical gardens

Visual simulation of chemical gardens

引用

computer Graphics International

作者： X. Wei F. Qiu W. Li S. Yoakum-Stover A. Kaufman Computer Science Department Iona College USA Center for Visual Computing and Department of Computer Science Stony Brook University USA Siemens AG Corporate Research and Development USA

关键词： Chemicals Biomembranes Crystals computer graphics Corrosion Computational modeling computer science visualization Osmosis Educational institutions

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Data mining in situ Gene expression patterns at cellular resolution

Data mining in situ Gene expression patterns at cellular res...

引用

2005 IEEE Computational Systems Bioinformatics Conference, Workshops and Poster Abstracts

作者： Carson, James Ju, Tao Thaller, Christina Bello, M. Kakadiaris, I. Warren, Joe Eichele, Gregor Chiu, Wah National Center for Macromolecular Imaging Baylor College of Medicine One Baylor Plaza Houston TX 77030 Verna and Marrs McLean Dept. of Biochemistry and Molecular Biology Baylor College of Medicine One Baylor Plaza Houston TX 77030 Dept. of Computer Science Rice University Houston TX Visual Computing Lab. Dept. of Computer Science University of Houston Houston TX Max Planck Institute of Experimental Endocrinology Hannover Germany

ISBN: (纸本)0769524427

Non-radioactive in situ hybridization (ISH) is a powerful technique for revealing gene expression in individual cells, the level of detail necessary for investigating how genes control cell type identity, cell differentiation, and cell-cell signaling. Although the availability of robotic ISH enables the expeditious determination of expression patterns for thousands of genes in serially sectioned tissues, a large collection of ISH images is, per se, of limited benefit. However, via accurate detection of expression strength and spatial normalization of expression location across different specimens, ISH images become a minable resource of annotated gene expression capable of advancing functional genomics in a mode similar to DNA sequence databases. We have developed computational methods to automate robotic ISH image annotation and applied these to over 200 genes throughout the postnatal mouse brain. Gene expression strengths were quantified for each cell tissue section images, and these images were subjected to atlas-based segmentation using a series of subdivision mesh maps that comprise our atlas of the postnatal mouse brain. With this common geometric representation of gene expression, patterns are automatically annotated and spatial searches successfully find the genes expressed in a similar fashion to custom query patterns. Cluster analysis of spatially normalized expression patterns identifies potential relationships in gene networks. Annotated gene expression patterns and query interfaces are publicly accessible at ***. © 2005 IEEE.

关键词： Data mining

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Data Mining in situ gene expression patterns at cellular resolution

Data Mining in situ gene expression patterns at cellular res...

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IEEE Computational Systems Bioinformatics Conference, CSB Workshops and Poster Abstracts

作者： J. Carson T. Ju C. Thaller M. Bello I. Kakadiaris J. Warren G. Eichele W. Chiu National Center for Macromolecular Imaging Baylor University College of Medicine Houston TX USA Department of Computer Science Rice University Houston TX USA Verna and Marrs McLean Department of Biochemistry and Molecular Biology Baylor University College of Medicine Houston TX USA Visual Computing Lab Department of Computer Science University of Houston Houston TX USA Max-Planck-Institut of Experimental Endocrinology Hanover Germany

Non-radioactive in situ hybridization (ISH) is a powerful technique for revealing gene expression in individual cells, the level of detail necessary for investigating how genes control cell type identity, cell differentiation, and cell-cell signaling. Although the availability of robotic ISH enables the expeditious determination of expression patterns for thousands of genes in serially sectioned tissues, a large collection of ISH images is, per se, of limited benefit. However, via accurate detection of expression strength and spatial normalization of expression location across different specimens, ISH images become a minable resource of annotated gene expression capable of advancing functional genomics in a mode similar to DNA sequence databases. We have developed computational methods to automate robotic ISH image annotation and applied these to over 200 genes throughout the postnatal mouse brain. Gene expression strengths were quantified for each cell tissue section images, and these images were subjected to atlas-based segmentation using a series of subdivision mesh maps that comprise our atlas of the postnatal mouse brain. With this common geometric representation of gene expression, patterns are automatically annotated and spatial searches success fully find the genes expressed in a similar fashion to custom query patterns. Cluster analysis of spatially normalized expression patterns identifies potential relationships in gene networks. Annotated gene expression patterns and query interfaces are publicly accessible at wv/spl bsol/w. geneattas. org.

关键词： Data mining Gene expression Mice Signal resolution Robots Genomics Bioinformatics DNA Sequences Image databases

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Landmark-driven, atlas-based segmentation of mouse brain tissue images containing gene expression data

引用

7th International Conference on Medical Imaging and computer Assisted Intervention, MICCAI 2004

作者： Kakadiaris, Ioannis A. Bello, Musodiq Arunachalam, Shiva Kang, Wei Ju, Tao Warren, Joe Carson, James Chiu, Wah Thaller, Christina Eichele, Gregor Visual Computing Lab Dept of Computer Science Univ of Houston HoustonTX United States Dept of Computer Science Rice University HoustonTX United States Verna and Marrs McLean Dept of Biochemistry Baylor College of Medicine HoustonTX United States Max Planck Institute of Experimental Endocrinology Hannover Germany

ISBN: (纸本)3540229760

To better understand the development and function of the mammalian brain, researchers have begun to systematically collect a large number of gene expression patterns throughout the mouse brain using technology recently developed for this task. Associating specific gene activity with specific functional locations in the brain anatomy results in a greater understanding of the role of the gene’s products. To perform such an association for a large amount of data, reliable automated methods that characterize the distribution of gene expression in relation to a standard anatomical model are required. In this paper, we present an anatomical landmark detection method that has been incorporated into an atlas-based segmentation. The addition of this technique significantly increases the accuracy of automated atlas-deformation. The resulting large-scale annotation will help scientists interpret gene expression patterns more rapidly and accurately. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Gene expression

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Automated characterization of gene expression patterns with an atlas of the mouse brain

Automated characterization of gene expression patterns with ...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： J.P. Carson T. Ju C. Thaller J. Warren M. Bello I. Kakadiaris W. Chiu G. Eichele Verna and Marrs McLean Department of Biochemistry and Molecular Biology Baylor University College of Medicine Houston TX USA Department of Computer Science Rice University Houston TX USA Visual Computing Lab Department of Computer Science University of Houston TX USA Max-Planck-Institut of Experimental Endocrinology Hanover Germany

A spatio-temporal map of gene activity in the brain would be an important contribution to the understanding of brain development, disease, and function. Such a resource is now possible using high-throughput in situ hybridization, a method for transcriptome-wide acquisition of cellular resolution gene expression patterns in serial tissue sections. However, querying an enormous quantity of image data requires computational methods for describing and organizing gene expression patterns in a consistent manner. In addressing this, we have developed procedures for automated annotation of gene expression patterns in the postnatal mouse brain.

关键词： Gene expression Mice Biology computing Pixel Computational biology Signal detection Image resolution computer science Diseases Organizing

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