The Human Body Atlas: High-Resolution, Functional Mapping of Voxel, Vector and Meta Datasets

人体图谱：体素、矢量和元数据集的高分辨率功能映射

• 批准号: 9919259
• 负责人: KATY BORNER
• 金额: $ 60万
• 依托单位: TRUSTEES OF INDIANA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-21 至 2020-06-20
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9919259
• 关键词: Anatomy; Artificial Intelligence; Atlases; Biology; Biometry; Cataloging; Catalogs; Cells; Collaborations; Communication; Data; Data Set; Ecosystem; Goals; Human; Human body; Image; Imagery; Individual; Infrastructure; Maps; Metadata; Methods; Modeling; Molecular; Organ; Resolution; Resources; Tissues; Visual; Work; base; cell type; design; human imaging; improved; interoperability; tool; vector

Project Summary/Abstract The ultimate goal of the HIVE MC-IU effort is to develop a common coordinate framework (CCF) for the healthy human body that supports the cataloguing, exploration, and download of different types of tissue and individual cell data. The CCF will use different visual interfaces in order to exploit human and machine intelligence to improve data exploration and communication. The proposed effort combines decades of expertise in data and network visualization, scientific visualization, biology, and biomedical data standards. The goal is to develop a highly accurate and extensible multidimensional spatial basemap of the human body with associated data overlays. This basemap will be designed for online exploration as an atlas of tissue maps composed of diverse cell types, developed in close collaboration with the HIVE MC-NYGC team. To implement this functionality, we will develop methods to map and connect metadata, pixel/voxel data, and extracted vector data, allowing users to “navigate” across multiple levels (whole body, organ, tissue, cells). MC-IU will work in close collaboration with the HIVE Infrastructure and Engagement Component (IEC) and tools components (TCs) to connect and integrate further computational, analytical, visualization, and biometric resources driven by spatial context.

项目总结/摘要 HIVE MC-IU工作的最终目标是制定一个共同的协调框架（CCF） 为健康的人体，支持编目，探索，和下载不同的 组织类型和单个细胞数据。国家合作框架将使用不同的可视界面， 利用人类和机器智能来改善数据探索和通信。的 拟议的努力结合了数十年的数据和网络可视化专业知识， 可视化、生物学和生物医学数据标准。我们的目标是开发一个高度准确的 和可扩展的人体多维空间底图以及相关数据 覆盖。此底图将作为组织地图集设计用于在线探索 由不同的细胞类型组成，与HIVE MC-NYGC密切合作开发 团队为了实现这个功能，我们将开发映射和连接元数据的方法， 像素/体素数据和提取的矢量数据，允许用户在多个级别上“导航” （整个身体、器官、组织、细胞）。MC-IU将与HIVE密切合作 基础设施和参与组件（IEC）和工具组件（TC）， 进一步整合计算、分析、可视化和生物识别资源， 空间背景。