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Proceedings of the 29th Australasian Computer Science conference - Volume 48

作者： Chris R. Johnson David M. Weinstein Scientific Computing and Imaging Institute School of Computing University of Utah Salt Lake City UT

ISBN: (纸本)9781920682309

Computers have changed the way we live, work, and even recreate. Now, they are transforming how we think about and treat human disease. In particular, advanced techniques in biomedical computing, imaging, and visualization are changing the face of biology and medicine in both research and clinical practice. The goals of biomedical computing, imaging and visualization are multifaceted. While some images and visualizations facilitate diagnosis, others help physicians plan surgery. biomedical simulations can help to acquire a better understanding of human physiology. Still other biomedical computing and visualization techniques are used for medical training. Within biomedical research, new computational technologies allow us to "see" into and understand our bodies with unprecedented depth and detail. As a result of these advances, biomedical computing and visualization will help produce exciting new biomedical scientific discoveries and clinical treatments. In this paper, we give an overview of the computational science pipeline for an application in neuroscience and present associated research results in medical imaging, modeling, simulation, and visualization [1].

关键词： biomedical computing visualization imaging problem solving environment

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From mesh generation to scientific visualization: An end-to-end approach to parallel supercomputing

From mesh generation to scientific visualization: An end-to-...

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2006 ACM/IEEE conference on Supercomputing, SC'06

作者： Tu, Tiankai Yu, Hongfeng Ramirez-Guzman, Leonardo Bielak, Jacobo Ghattas, Omar Ma, Kwan-Liu O'Hallaron, David R. Computer Science Department Carnegie Mellon University Pittsburgh PA 15213 United States Department of Computer Science University of California Davis CA 95616 United States Department of Civil and Environmental Engineering Carnegie Mellon University Pittsburgh PA 15213 United States Departments of Mechanical Engineering Biomedical Engineering and Computer Sciences Jackson School of Geosciences University of Texas at Austin Austin TX 78077 United States

ISBN: (纸本)0769527000

Parallel supercomputing has traditionally focused on the inner kernel of scientific simulations: the solver. The front and back ends of the simulation pipeline - -problem description and interpretation of the output - -have taken a back seat to the solver when it comes to attention paid to scalability and performance, and are often relegated to offline, sequential computation. As the largest simulations move beyond the realm of the terascale and into the petascale, this decomposition in tasks and platforms becomes increasingly untenable. We propose an end-to-end approach in which all simulation components - -meshing, partitioning, solver, and visualization - -are tightly coupled and execute in parallel with shared data structures and no intermediate I/O. We present our implementation of this new approach in the context of octree-based finite element simulation of earthquake ground motion. Performance evaluation on up to 2048 processors demonstrates the ability of the end-toend approach to overcome the scalability bottlenecks of the traditional approach. © 2006 IEEE.

关键词： Supercomputers

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Real-time multi-scale brain data acquisition, assembly, and analysis using an end-to-end OptIPuter

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2006年第8期22卷 1032-1039页

作者： Singh, Rajvikram Schwarz, Nicholas Taesombut, Nut Lee, David Jeong, Byungil Renambot, Luc Lin, Abel W. West, Ruth Otsuka, Hirornu Naito, Sei Peltier, Steven T. Martone, Maryann E. Nozaki, Kazunori Leigh, Jason Ellisman, Mark H. Univ Illinois Elect Visualizat Lab Chicago IL USA Univ Calif San Diego Natl Ctr Micoscopy & Imaging Res San Diego CA USA Univ Illinois Elect Visualizat Lab Chicago IL USA Univ Calif San Diego Dept Comp Sci & Engn San Diego CA USA Osaka Univ Cybermedia Ctr Osaka Japan KDDI Corp Chiyoda Ku Tokyo 1028460 Japan KDDI Labs Fujimino Saitama 3568502 Japan

At iGrid 2005 we demonstrated the transparent operation of a biology experiment on a test-bed of globally distributed visualization, storage, computational, and network resources. These resources were bundled into a unified platform by utilizing dynamic lambda allocation, high bandwidth protocols for optical networks, a Distributed Virtual Computer (DVC) [N. Taesombut, A. Chien, Distributed Virtual Computer (DVC): Simplifying the development of high performance grid applications, in: Proceedings of the Workshop on Grids and Advanced Networks, GAN 04, Chicago, IL, April 2004 (held in conjunction with the IEEE Cluster computing and the Grid (CCGrid2004) conference)], and applications running over the Scalable Adaptive Graphics Environment (SAGE) [L. Renambot, A. Rao, R. Singh, B. Jeong, N. Krishnaprasad, V. Vishwanath, V. Chandrasekhar, N. Schwarz, A. Spale, C. Zhang, G. Goldman, J. Leigh, A. Johnson, SAGE: The Scalable Adaptive Graphics Environment, in: Proceedings of WACE 2004, 23-24 September 2004, Nice, France, 2004]. Using these layered technologies we ran a multi-scale correlated microscopy experiment [M.E. Maryann, T.J. Deerinck, N. Yamada, E. Bushong, H. Ellisman Mark, Correlated 3D light and electron microscopy: Use of high voltage electron microscopy and electron tomography for imaging large biological structures, Journal of Histotechnology 23 (3) (2000) 261-270], where biologists imaged samples with scales ranging from 20X to 5000X in progressively increasing magnification. This allows the scientists to zoom in from entire complex systems such as a rat cerebellum to individual spiny dendrites. The images used spanned multiple modalities of imaging and specimen preparation, thus providing context at every level and allowing the scientists to better understand the biological structures. This demonstration attempts to define an infrastructure based on OptIPuter components which would aid the development and design of collaborative scientific experiments, appli

关键词： graphics clusters multi-scale correlated microscopy montage images HDTV streaming telescience tile displays tiled displays optical networks scientific visualization remote instrumentation

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Image Based Temporal Registration of MRI Data for Medical visualization

Image Based Temporal Registration of MRI Data for Medical Vi...

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IEEE International conference on Image Processing

作者： Meghna Singh Richard Thompson Anup Basu Jana Rieger Mrinal Mandal Departments of Electrical & Computer Engineering University of Alberta Edmonton AB Canada Biomedical Engineering University of Alberta Edmonton AB Canada Computing Science University of Alberta Edmonton AB Canada Rehabilitation Medicine University of Alberta Edmonton AB Canada

The capability of creating video data from MRI has many advantages in visualization for medical practitioners, including (i) not subjecting patients to harmful radiations, (ii) being able to monitor patients at short inter-exam time intervals, and (iii) being able to capture 3D volume data. The quality and speed with which MRI data can be acquired, however, poses a challenge towards supporting good quality visualization. In this work we present results from our preliminary attempts at enhancing the temporal resolution of video captured via MRI. Our initial focus is on visualization of swallowing and associated problems that are broadly categorized as Dysphagia. We present a method to register data from multiple swallows to generate high temporal resolution MRI videos.

关键词： Magnetic resonance imaging biomedical imaging Data visualization Spatial resolution Endoscopes Biological tissues biomedical engineering Data engineering X-ray imaging Ultrasonic imaging

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Parallel visualization of Visible Chinese Human with Extremely Large Datasets

Parallel Visualization of Visible Chinese Human with Extreme...

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

作者： Liu Qian Gong Hui Luo Qingming Hubei Bioinformatics and Molecular Imaging Key Laboratory Huazhong University of Science and Technology Wuhan China

Single sectional anatomy image of Visible Chinese Human datasets achieved recently in First Military Medical University is almost 127 MByte. The total datasets are estimated to be 1.1 TByte if 48 bits color image is stored. Personal computer and graph workstation with multiple CPUs are also impossible to process extremely large datasets. Therefore the challenge is to visualize the extremely large datasets efficiently. Visible Chinese Human datasets are so massive in size they require the use of parallel computing resources for effective visualization. At present a parallel visualization program has been developed based on parallelism visualization toolkit (pVTK) on high performance cluster to solve the problem. The visualization results and performance demonstrate that the parallel program we developed provides a promising solution of handling extremely large datasets

关键词： Humans Parallel processing Data visualization Rendering (computer graphics) Biological system modeling Object oriented modeling Anatomy biomedical imaging Microcomputers Workstations

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Fast Volume Rendering for Medical Image

Fast Volume Rendering for Medical Image

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

作者： Hu Ying Xu Xin-he Automation Research Center Dalian Maritime University Dalian Liaoning China

In orders to improve the rendering speed of ray casting and make this technique a practical routine in medical applications, two new and improved techniques are described in this paper. First, an integrated method using "proximity clouds" technique is applied to speed up ray casting. The second technique for speeding up the 3D rendering is done through a parallel implementation based on "single computer multi CPU" model Four groups of CT data sets have been used to validate the improvement of the rendering speed. The result shown that the interactive rendering speed is up to 6-10 fps, which is almost real-time making our algorithm practical in medical visualization routine

关键词： Rendering (computer graphics) biomedical imaging Casting Medical services biomedical equipment Clouds Concurrent computing Computed tomography Computer graphics Data visualization

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Interactive & Immersive VR Image Processing and visualization

Interactive & Immersive VR Image Processing and Visualizatio...

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International conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Ch Lim C Indhumathi Yy Cai School of Mechanical & Aerospace Engineering Nanyang Technological University Singapore

Volume rendering is a computerized visualization technique that can be used to identify critical portions and specific regions of interest in various applications including medicine or biology. Localization and segmentations can be conducted and rendered dynamically such that navigation and operations within the volumetric dataset can be implemented. This paper describes our work on immersive VR image processing and visualization. A system is being developed with motion tracking and a pen-like stylus in this project in order to assist the bio-medical science research. This will provide a six degree-of-freedom 3D motion control that eases the control for volume manipulation and data extraction in a 3D environment. Together with a stereovision system, it will provide the user with a full 3D interactive environment in virtual reality (VR) for medical and cell biological applications

关键词： Virtual reality Image processing visualization Rendering (computer graphics) biomedical imaging Motion control Biology computing Application software Image segmentation Navigation

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GAVis: a Tool for visualization and Control of Genetic Algorithms for -omic Data Analysis

GAVis: a Tool for Visualization and Control of Genetic Algor...

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

作者： T.H. Stokes J.H. Phan W.M. Feng G. Tuteja M.D. Wang Wallace H. Coulter Biomedical Engineering Department Georgia Institute of Technology and Emory University Atlanta GA USA

A visualization and steering application, GAVis, has been developed to aid in understanding the behavior of and guiding the convergence of genetic algorithms running in parallel over long time periods. When classification techniques such as support vector machines (SVMs) paired with complete leave-one-out validation are used as a fitness function for identification of markers in -omic data, the time to complete one generation can exceed an hour on modern high-performance computing clusters. Separate solution populations on "islands" can help maintain a more diverse solution space and conveniently map to compute nodes on a cluster. Adjustments can be made at runtime to speed the convergence of genetic algorithms by stimulating lagging island populations with migrations of high-performing individuals or by selectively increasing mutation rates

关键词： Data visualization Genetic algorithms Data analysis Genetic mutations biomedical engineering Support vector machines Support vector machine classification Runtime Bioinformatics Diseases

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3D Medical Imaging Computation and Analysis Platform

3D Medical Imaging Computation and Analysis Platform

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IEEE International conference on Industrial Technology (ICIT)

作者： Huiguang He Jie Tian Mingchang Zhao Jian Xue Ke Lu Key Laboratory of Complex Systems and Intelligence Science Chinese Academy and Sciences China College of Computing & Communication Engineering Chinese Academy of Sciences China

Currently in the community of medical imaging computation and analysis, there exist several excellent toolkits for various tasks. For example, VTK (http://***) is the most famous visualization tool and ITK (http://***) plays an important role in the segmentation and registration of medical images. These toolkits can assist the doctors to get the more accurate diagnosis, and help the researchers to get the more powerful capability of medical image processing. However, they are separate and style-various. Even for VTK and ITK, which are designed by the same company, users have to familiarize the two completely different coding styles. In this situation, using all of these toolkits is difficult. In this study, we will introduce 3D medical imaging computation and analysis platform (3DMed), which provides powerful functions such as image preprocessing, virtual cutting, surface rendering, volume rendering, manipulation and virtual endoscopy. The functional module description, system design and the visualization algorithm is demonstrated. The system can be widely applied to processing and analysis of CT and MR images.

关键词： biomedical imaging Image analysis visualization Rendering (computer graphics) Image segmentation Medical diagnostic imaging biomedical image processing Image coding Endoscopes System analysis and design

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3D Construction of Endoscopic Images Based on Computational Stereo

3D Construction of Endoscopic Images Based on Computational ...

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Annual Northeast Bioengineering conference

作者： Qiang Liu R.J. Sclabassi Ning Yao Mingui Sun Department of Neurological Surgery University of Pittsburgh Pittsburgh PA USA Department of Biomedical Engineering University of Pittsburgh Pittsburgh PA USA Department of Electrical Engineering University of Pittsburgh Pittsburgh PA USA

Endoscopic surgery, a typical example ofminimally invasive surgery, has changed the traditional surgicalprocedure in the way of accessing the visual informationavailable on the corporal site. Its development heavily relies onthe improvement of the visualization technologies. Three-dimensional (3D) image system that is capable ofproviding more depth cues, therefore, has a potentially strongimpact on the current 2D image guiding technology. Unlikemost other systems that utilize stereoendoscopes with dual lens, we study the feasibility of 3D image construction fromsingle-lens endoscopic video by exploring the theory of multipleview geometry. We coupled a regular endoscope to aposition-measurement equipment to provide extrinsicparameters of the acquired images. With the available multipleview geometric algorithms, depth maps were constructed fromtwo consecutively collected images. We present theexperimental results and conclude that computational stereopsishas a great potential in building 3D endoscopic image systemsfor both surgical aiding and training.

关键词： Endoscopes Cameras Minimally invasive surgery biomedical measurements biomedical computing visualization Lenses Geometry Buildings Helium

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