GOAL BASED ALOGRITHMS FOR 3 DIMENSIONAL ANALYSIS AND VISUALIZATION

这个项目的长期目标是将新兴的方法从 计算机图形学和数据收集的扩展技术水平， 三维大脑的建模、分析与可视化 结构。其目的是开发新的算法并创建一套 用于收集和与多值交互的模块化和可重复使用的工具 解剖信息，以及开发工具来帮助 传播这一信息。通过开发新类型的计算， 其目的是最终实现新型诊断程序和 供大脑研究人员和健康从业者使用的方法。 本项目有五个相关研究领域： 1)继续开发“以目标为基础”的数据采集方法； 2)从扩散张量数据中阐明微结构， 3)多值组织分类算法， 4)半沉浸式可视化算法和交互方法 在“响应式工作台”上显示和数据采集 5)新型的多值可视化方法，如“画图” 视觉化。 该项目涉及磁共振微成像，以及双光子和 共聚焦显微镜。使用来自Atlas的高分辨率解剖数据 项目和来自连接项目的核磁共振核心和光学数据， 组织将通过它们的化学物质进行分类和可视化 成分和微观结构。算法和注释子集 可视化数据将通过出版物和 网络。

The long term aim of this project is to take emerging methods from computer graphics and extend state of the art in data collection, modeling, analysis and visualization of three-dimensional brain structures. The intent is to develop new algorithms and create a set of modular and re-usable tools for collect and interacting with multivalued anatomic information, as well as developing tools that aid in dissemination of this information. By developing new types of computation, the intent is to ultimately enable new types of diagnostic procedures and approaches for use by brain researchers and health practitioners. There are five related research areas in this project: 1) continued development of "goal-based" data acquisition methods, 2) elucidation of microstructure from diffusion tensor data, 3) multivalued tissue classification algorithms, 4) semi-immersive visualization algorithms and interaction methods for display and data acquisition on a "Responsive Workbench" and 5) new types of multivalued visualization methods, such as "painterly" visualization. The project involves magnetic resonance micro-imaging, and two-photon and confocal microscopy. Using high resolution anatomical data from the Atlas Project and MRI Core and optical data from the Connectivity Project, tissues will be classified and visualized through their chemical composition and microstructure. The algorithms and an annotated subsets of the visualized data will be disseminated through publications and via the web.