The Experience and Practice of Developing a Brain Functional Analysis System Using ICA on a Grid Environment
The Experience and Practice of Developing a Brain Functional Analysis System Using ICA on a Grid Environment
复制标题
网格环境下ICA开发脑功能分析系统的经验与实践
DOI：
10.1007/3-540-36184-7_11
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发表时间：
2002
期刊：
影响因子：
--
通讯作者：
S. Shimojo
中科院分区：
文献类型：
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作者：
T. Kaishima;Y. Mizuno;S. Date;S. Shimojo
为了有效和早期诊断脑部疾病，我们一直在开发网格环境下的脑功能分析系统。直到最近，神经科学家已经提出并开发了许多分析大脑功能的方法。虽然最近提出的分析方法往往是计算密集型的，但在大多数情况下，它们是在单处理器的基础上执行的，例如商用个人计算机。在网格环境下开发的系统使研究人员和医生能够整合各种地理分布的资源，并在现实的时间段内分析大脑功能数据，而无需详细了解网格。通过本文，我们展示了建立在网格上的系统有能力提供足够的计算能力来执行有前途的脑功能分析，如独立成分分析（ICA）。此外，我们主要从应用程序构建的角度介绍了与开发网格化脑功能分析系统相关的经验和实践。
For the effective and early diagnosis of brain diseases, we have been developing a brain functional analysis system on a Grid environment. Until recently, neuroscientists have proposed and exploited numerous methods for the analysis of brain function. Although recently proposed analysis methods tend to be computationally-intensive, they are performed, in most cases, on a single-processor basis such as a commodity personal computer. The system developed on the Grid environment allows researchers and medical doctors to integrate a variety of geographically distributed resources and to analyze functional brain data in a realistic time period without detailed knowledge of the Grid. Through this paper, we show that the system built on the Grid has the capability to deliver enough computational power to perform promising brain functional analysis such as Independent Component Analysis (ICA). In addition, we present the experience and practice related to developing a Grid-enabled system for brain functional analysis mainly from the viewpoint of application building.