用于脑网络连接加权图比较的可视分析系统设计与实现

Design and Implementation of Visual Analysis System for Brain Network Weighted Graph Comparison

摘要:

人脑功能网络的研究是近十年生物学领域的重要课题,可视化工具作为数据分析的重要手段,在脑科学研究中有着举足轻重的地位。然而现有的脑功能网络可视化工具存在信息获取效率低、功能单一等问题。针对以上问题,设计并实现了一款用于脑网络连接加权图比较的可视分析系统,帮助研究人员探索不同群组间的差异。首次提出并使用一种用于脑网络连接加权图比较的新可视化方法,针对该方法的用户评估表明,改进后的可视方法在做对比分析任务时更有效。此外,系统将数据挖掘与可视化相结合,增强了群组间差异的表现形式。并且提供了多视图协同等一系列交互方式供研究人员自主探索。最后使用了两组公开数据集进行案例分析,验证了系统的有用性和高效性。

Abstract:

The study of human brain functional network has been an important subject of biology in recent decades. As an important method of data analysis, visualization tools play a significant role in the study of brain science. However, the existing visualization tools of brain functional network have some problems, such as low information acquisition efficiency and single function. To solve the above problems, a visual analysis system was designed and implemented for comparing weighted graphs of brain network connections to help researchers explore the differences between different groups. A new visualization method for the comparison of weighted graphs of brain network is proposed and used for the first time. The user evaluation of this method shows that the new visualization method is more effective in the task of contrast analysis. In addition, the system combines data mining with visualization to enhance the presentation of differences among groups. Moreover, it provides a series of interactive ways such as multi-view collaboration for researchers to explore independently. Finally, two sets of public data sets are used for case analysis to verify the usefulness and efficiency of the system.