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Simulating Soft Tissues using a GPU approach of the Mass-Spring Model

Simulating Soft Tissues using a GPU approach of the <i>Mass<...

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Conference on Virtual Reality 2010

作者： Diaz Leon, Christian Andres Eliuk, Steven Trefftz Gomez, Helmuth EAFIT Univ Virtual Real Lab Medellin Colombia Univ Alberta AMMI Edmonton AB T6G 2M7 Canada

ISBN: (纸本)9781424462582

The recent advances in the fields such as modeling bio-mechanics of living tissues, haptic technologies, computational capacity, and graphics realism have created conditions necessary in order to develop effective surgical training using virtual environments. However, virtual simulators need to meet two requirements, they need to be real-time and highly realistic. The most expensive computational task in a surgical simulator is that of the physical model. The physical model is the component responsible to simulate the deformation of the anatomical structures and the most important factor in order to obtain realism. In this paper we present a novel approach to virtual surgery. The novelty comes in two forms: specifically a highly realistic mass-spring model, and a GPU based technique, and analysis, that provides a nearly 80x speedup over serial execution and 20x speedup over CPU based parallel execution.

关键词： GPU Virtual Surgery Mass-Spring parallel Computing

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Volume graphics 2010 - 8th ieee/EG International symposium on Volume graphics

Volume Graphics 2010 - 8th IEEE/EG International Symposium o...

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8th ieee/EG International symposium on Volume graphics, Volume graphics 2010, Co-located with the Annual Conference of the European Association for Computer graphics, Eurographics 2010

ISBN: (纸本)9783905674217

The proceedings contain 16 papers. The topics discussed include: a new sampling scheme for slice based volume rendering;multi-layer volume ray casting on GPU;wavelet-based multi resolution isosurface rendering;split-voxel: a simple discontinuity-preserving voxel representation for volume rendering;real-time surface analysis and tagged material cleansing for virtual colonoscopy;slimming brick cache strategies for seismic horizon propagation algorithms;volumetric evaluation of meshless data from smoothed particle hydrodynamics simulations;concurrent volume visualization of real-time fMRI;fast volumetric data exploration with importance-based accumulated transparency modulation;multi-dimensional reduction and transfer function design using parallel coordinates;a survey of transfer functions suitable for volume rendering;feature-driven ambient occlusion for direct volume rendering;and GPU-supported lossless compression scheme for rendering time-varying volume data.

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Hardware-assisted Projected Tetrahedra

Hardware-assisted Projected Tetrahedra

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12th Eurographics/ieee-VGTC symposium on visualization, EuroVis 2010

作者： Maximo, A. Marroquim, R. Farias, R. COPPE Federal University of Rio de Janeiro Brazil

We present a flexible and highly efficient hardware-assisted volume renderer grounded on the original Projected Tetrahedra (PT) algorithm. Unlike recent similar approaches, our method is exclusively based on the rasterization of simple geometric primitives and takes full advantage of graphics hardware. Both vertex and geometry shaders are used to compute the tetrahedral projection, while the volume ray integral is evaluated in a fragment shader;hence, volume rendering is performed entirely on the GPU within a single pass through the pipeline. We apply a CUDA-based visibility ordering achieving rendering and sorting performance of over 6 M Tet/s for unstructured datasets. Furthermore, as each tetrahedron is processed independently, we employ a data-parallel solution which is neither bound by GPU memory size nor does it rely on auxiliary volume information. In addition, iso-surfaces can be readily extracted during the rendering process, and time-varying data are handled without extra burden. © The Eurographics Association and Blackwell Publishing Ltd.

关键词： graphics processing unit

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Multi-dimensional reduction and transfer function design using parallel coordinates

Multi-dimensional reduction and transfer function design usi...

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作者： Zhao, X. Kaufman, A. Stony Brook University United States

ISBN: (纸本)9783905674217

Multi-dimensional transfer functions are widely used to provide appropriate data classification for direct volume rendering. Nevertheless, the design of a multi-dimensional transfer function is a complicated task. In this paper, we propose to use parallel coordinates, a powerful tool to visualize high-dimensional geometry and analyze multivariate data, for multi-dimensional transfer function design. This approach has two major advantages: (1) Combining the information of spatial space (voxel position) and parameter space;(2) Selecting appropriate high-dimensional parameters to obtain sophisticated data classification. Although parallel coordinates offers simple interface for the user to design the high-dimensional transfer function, some extra work such as sorting the coordinates is inevitable. Therefore, we use a local linear embedding technique for dimension reduction to reduce the burdensome calculations in the high dimensional parameter space and to represent the transfer function concisely. With the aid of parallel coordinates, we propose some novel high-dimensional transfer function widgets for better visualization results. We demonstrate the capability of our parallel coordinates based transfer function (PCbTF) design method for direct volume rendering using CT and MRI datasets. © The Eurographics Association 2010.

关键词： Transfer functions

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A parallel cellular automata with label priors for interactive brain tumor segmentation

A parallel cellular automata with label priors for interacti...

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Annual ieee symposium on Computer-Based Medical Systems

作者： Edward Kim Tian Shen Xiaolei Huang Department of Computer Science and Engineering Lehigh University Bethlehem PA USA

We present a novel method for 3D brain tumor volume segmentation based on a parallel cellular automata framework. Our method incorporates prior label knowledge gathered from user seed information to influence the cellular automata decision rules. Our proposed method is able to segment brain tumor volumes quickly and accurately using any number of label classifications. Exploiting the inherent parallelism of our algorithm, we adopt this method to the graphics Processing Unit (GPU). Additionally, we introduce the concept of individual label strength maps to visualize the improvements of our method. As we demonstrate in our quantitative and qualitative results, the key benefits of our system are accuracy, robustness to complex structures, and speed. We compute segmentations nearly 45× faster than conventional CPU methods, enabling user feedback at interactive rates.

关键词： graphics processing unit Tumors Image segmentation Automata Three dimensional displays visualization Magnetic resonance imaging

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An improved visual inspection system using visual servo

An improved visual inspection system using visual servo

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ieee/SICE International symposium on System Integration

作者： Chuantao Zang Koichi Hashimoto Graduate School of Information Sciences University of Tohoku Japan

In this paper we present an improved automatic visual inspection system. In this system, homography based visual servo is used to accurately locate the camera position and attitude so that a template matching inspection can be realized. To improve the visual servo system's performance, we propose a combination strategy of a GPU based Efficient Second-order Minimization (GPU-ESM) algorithm and a GPU based Scale Invariant Feature Transform (SIFT) algorithm. By utilizing the parallel processing capability of a GPU, system processing speed and reliability has been greatly improved. In this paper, the implementation details of the visual inspection system are presented. The performance of the proposed combination strategy is evaluated with experimental data.

关键词： visualization graphics processing unit Servomotors Cameras Kernel Inspection Tracking

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Visualizing complex dynamics in many-core accelerator architectures

Visualizing complex dynamics in many-core accelerator archit...

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ieee International symposium on Performance Analysis of Systems and Software

作者： Aaron Ariel Wilson W. L. Fung Andrew E. Turner Tor M. Aamodt University of British Columbia Vancouver BC Canada

ISBN: (纸本)9781424460236;9781424460229

While many-core accelerator architectures, such as today's graphics Processing Units (GPUs), offer orders of magnitude more raw computing power than contemporary CPUs, their massive parallelism often produces complex dynamic behaviors even with the simplest applications. Using a fixed set of hardware or simulator performance counters to quantify behavior over a large interval of time such as an entire application execution run or program phase may not capture this behavior. Software and/or hardware designers may consequently miss out on opportunities to optimize for better performance. Similarly, significant effort may be expended to find metrics that explain anomalous behavior in architecture design studies. Moreover, the increasing complexity of applications developed for today's GPU has created additional difficulties for software developers when attempting to identify bottlenecks of an application for optimization. This paper presents a novel GPU performance visualization tool, AerialVision, to address these two problems. It interfaces with the GPGPU-Sim simulator to capture and visualize the dynamic behavior of a GPU architecture throughout an application run. Similar to existing performance analysis tools for CPUs, it can annotate individual lines of source code with performance statistics to simplify the bottleneck identification process. To provide further insight, AerialVision introduces a novel methodology to relate pathological dynamic architectural behaviors resulting in performance loss with the part of the source code that is responsible. By rapidly providing insight into complex dynamic behavior, AerialVision enables research on improving many-core accelerator architectures and will help ensure applications written for these architectures reach their full performance potential.

关键词： visualization Accelerator architectures Application software Hardware Computer architecture graphics Concurrent computing parallel processing Computational modeling Counting circuits

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BIOMEDICAL IMAGING ECOSYSTEM AND THE ROLE OF THE GPU

BIOMEDICAL IMAGING ECOSYSTEM AND THE ROLE OF THE GPU

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ieee International symposium on Biomedical Imaging - From Nano to Macro

作者： Powell, Kimberly NVIDIA Corp. United States

ISBN: (纸本)9781424439317

The biomedical imaging chain is continuously being challenged to reconstruct, analyze, and visualize increasing amounts of data in shorter amounts of time. parallel computing on multi-core devices and clustered computers has allowed for continued innovation of compute and processing technologies but not without facing serious constraints of cost, space, and power consumption. Over the last three years the graphics processing unit (GPU) and its increased programmability has played an integral role in defining a new dimension to parallel computing with its single chip, many-core architecture as well as evolving the graphics pipeline to enhance visualization techniques. Image reconstruction, segmentation and registration algorithms architected to take advantage of the GPU parallel architecture not only realize massive processing speedups but also set the stage for scalability. High resolution rendering of 3D and 4D datasets are navigated in interactive, real-time approaches. Real time ray tracing and 3D stereoscopic solutions bring increased realism to images. Understanding the optimized mix of GPU and CPU, both in the sense of hardware and software, is necessary for imaging applications to innovate, realize cost/performance efficiency and continue to enhance visualization. Several approaches for GPU programmability are available and will be explored. Innovations in the compute, graphics and visualization space will be discussed to show the relevance of the GPU throughout the imaging chain.

关键词： graphics processing unit real time reconstruction CUDA

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parallel tag clouds to explore and analyze faceted text corpora

Parallel tag clouds to explore and analyze faceted text corp...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Collins, Christopher Viégas, Fernanda B. Wattenberg, Martin University of Toronto Canada IBM Research

ISBN: (纸本)9781424452835

Do court cases differ from place to place? What kind of picture do we get by looking at a country's collection of law cases? We introduce parallel Tag Clouds: a new way to visualize differences amongst facets of very large metadata-rich text corpora. We have pointed parallel Tag Clouds at a collection of over 600,000 US Circuit Court decisions spanning a period of 50 years and have discovered regional as well as linguistic differences between courts. The visualization technique combines graphical elements from parallel coordinates and traditional tag clouds to provide rich overviews of a document collection while acting as an entry point for exploration of individual texts. We augment basic parallel tag clouds with a details-in-context display and an option to visualize changes over a second facet of the data, such as time. We also address text mining challenges such as selecting the best words to visualize, and how to do so in reasonable time periods to maintain interactivity. ©2009 ieee.

关键词： visualization

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VAST 09 - ieee symposium on Visual Analytics Science and Technology, Proceedings

VAST 09 - IEEE Symposium on Visual Analytics Science and Tec...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

ISBN: (纸本)9781424452835

The proceedings contain 56 papers. The topics discussed include: interactive visual clustering of large collections of trajectories;proximity-based visualization of movement trace data;guided analysis of hurricane trends using statistical processes integrated with interactive parallel coordinates;finding comparable temporal categorical records: a similarity measure with an interactive visualization;a visual analytics system for radio frequency fingerprinting-based localization;combining automated analysis and visualization techniques for effective exploration of high-dimensional data;two-stage framework for visualization of clustered high dimensional data;model space visualization for multivariate linear trend discovery;parallel tag clouds to explore and analyze faceted text corpora;describing story evolution from dynamic information streams;VAST contest dataset use in education;evaluating visual analytics systems for investigative analysis: deriving design principles from a case study;and visual analysis of graphs with multiple connected components.

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