Building Geometric Databases for Anatomy-Based Spatial Queries

为基于解剖学的空间查询构建几何数据库

• 批准号: 0743691
• 负责人: Tao Ju
• 金额: $ 78.1万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-15 至 2012-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0743691&HistoricalAwards=false
• 关键词: Building; Geometric; Databases; Anatomy; Based

This grant aims to develop an atlas-based database architecture suited for organizing 3D anatomical images for efficient spatial queries. Utilizing a new form of atlas, the project will develop tools for accurate and efficient alignment of 3D images collected from a large number of subjects with varying anatomical shapes. The resulting database will facilitate convenient, web-based spatial queries of functional, metabolic, mechanical, and structural data within customizable regions of interest among stored images. As a test-bed application, the project will construct two web-based databases of 3D gene expression patterns for the mouse brain and heart from stacks of 2D tissue sections.At the heart of the architecture is a new type of geometric atlas, represented as a subdivision mesh, which models the partitioning and interior of an anatomical region of interest, such as the brain. The geometric and multi-resolution structure of the atlas allows for flexible registration onto individual subjects with varying anatomical shapes, and enables fast, multi-level comparison of registered data. The tools for constructing, populating, and querying atlas-based databases will be made freely available online to be easily integrated with existing databases for augmented spatial querying capabilities.The use of biological imaging in science continues to grow, and it has thus become critical to many research efforts to be able to efficiently utilize the enormous resources of spatial information being generated. The gene expression databases resulted from the project will enable querying and clustering of genes based on similarity of 3D expression patterns, which may lead to significant breakthroughs in understanding biological processes. The long term goal of this project is to facilitate collaborative knowledge discovery across subjects, image modalities, and geographical locations.

该资助旨在开发一种基于图集的数据库架构，适合组织 3D 解剖图像以进行高效的空间查询。该项目将利用一种新形式的图集，开发工具来准确、高效地对齐从大量具有不同解剖形状的受试者中收集的 3D 图像。由此产生的数据库将有助于对存储图像中可定制的感兴趣区域内的功能、代谢、机械和结构数据进行方便的、基于网络的空间查询。作为一个测试平台应用程序，该项目将从一堆 2D 组织切片中构建两个基于网络的小鼠大脑和心脏 3D 基因表达模式数据库。该架构的核心是一种新型几何图谱，表示为细分网格，用于模拟感兴趣的解剖区域（例如大脑）的分区和内部。图谱的几何和多分辨率结构允许灵活注册到具有不同解剖形状的个体受试者，并能够对注册数据进行快速、多层次的比较。用于构建、填充和查询基于图集的数据库的工具将免费在线提供，以便与现有数据库轻松集成，以增强空间查询功能。生物成像在科学中的使用不断增长，因此对于为了能够有效地利用正在生成的巨大空间信息资源，进行了许多研究工作。该项目产生的基因表达数据库将能够基于3D表达模式的相似性对基因进行查询和聚类，这可能会在理解生物过程方面带来重大突破。该项目的长期目标是促进跨学科、图像模式和地理位置的协作知识发现。