CISE Research Instrumentation: Acquisition of a Compute Server for Image Analysis Research that Emphasize Empirical Performance Characterization

9729904 Bowyer，Kevin W. 南佛罗里达大学 CISE Research Instrumentation：为强调实证性能表征的图像分析研究收购计算服务器 这项研究仪器补助金用于购买一台计算机 USF实验室研究网络的服务器，配备四个250 Mhz UltraSparc 处理器、1GB主内存、35 GB格式化磁盘空间和磁带驱动器， 这将使以下项目成为可能：-边缘检测器的自动性能评估，-从2D视图恢复非刚性运动和结构，-感知组织模块的性能评估，以及-从脑MRI自动提取肿瘤体积。该项目涉及四个图像分析任务：边缘检测器算法的性能分析，图像序列中的非刚性运动分析算法，感知分组算法的开发和分析，以及基于聚类的磁共振图像分割算法的开发。这些任务在计算上都是昂贵的。此外，研究的经验表征的算法的性能进行了强调。 这种类型的研究提出了巨大的计算需求，这是不可行的进行这种类型的研究与典型的工作站，个人用户将在他们的办公桌上。为了使这项研究切实可行，USL将获得一个计算服务器，它将提供更大的计算能力。这台计算机服务器将在研究项目之间共享。每个项目都具有创新性，将产生高质量的出版物。此外，这些项目中创建的数据集和经验方法将对未来的研究产生重大影响。

9729904 Bowyer, Kevin W. University of South Florida CISE Research Instrumentation: Acquisition of a Compute Server for Image Analysis Research that Emphasizes Empirical Performance Characterization This research instrumentation grant contributes to the purchase of a compute server for the lab research network at USF with four 250 Mhz UltraSparc Processors, 1GB main memory, 35 GB of formatted disk pace, and a tape drive, which will enable the following projects:- Automated Performance Evaluation of Edge Detectors,- Nonrigid Motion and Structure Recovery from 2D Views, - Performance Evaluation of Perceptual Organization Modules, and - Automatic Tumor Volume Extraction from Brain MRI. This project deals with four image analysis tasks: performance analysis of edge detector algorithms, algorithms for analysis of non-rigid motion in image sequences, the development and analysis of perceptual grouping algorithms, and the development of clustering-based algorithms for the segmentation of magnetic resonance images. These tasks are all computationally expensive. In addition, the studied empirical characterization of the performance of the algorithms is emphasized. This style of research presents enormous computational demands, and it is not feasible to conduct this style of research with the typical workstation that an individual user would have on their desk. To make it practical to carry out this research, USL will acquire a compute server that will provide much greater computational power. This compute server will be shared among the research projects. Each of the projects is innovative and will lead to high-quality publications. In addition, the data sets and empirical methods that are created in these projects will have substantial impact on future research.