Collaborative Research: CI-P: Computationally-enhanced optical imaging infrastructure

合作研究：CI-P：计算增强光学成像基础设施

• 批准号: 1059314
• 负责人: Eric Miller
• 金额: $ 1.54万
• 依托单位: Tufts University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-03-01 至 2012-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1059314&HistoricalAwards=false
• 关键词: Collaborative; Research; CI; Computationally; enhanced

Optical imaging is increasingly used in biomedical research for its unique advantages in terms of sensitivity, specificity, resolution, and versatility, as compared with other imaging modalities. Optical imaging spans multiple scales, from macroscopic imaging using bioluminescence and fluorescence which collect data at millimeter level to microscopic imaging at the micrometer level in both 2D and 3D spaces. Combined with high-throughput and staining techniques, optical images are often acquired in large numbers over several channels. As a result, for optical imaging methods to be of maximal use in biomedical research, computational enhancement of optical imaging has become a necessity for data management and effective information extraction.This project initializes and adopts a multi-disciplinary approach to planning the creation of a community infrastructure for computationally enhanced optical imaging. The planning stage includes a larger workshop and smaller, targeted meetings, and discussions to solicit input from computational scientists, biomedical researchers, and engineers concerning the establishment, functionality, operational processes and user access of a computationally enhanced optical imaging infrastructure. The planned community infrastructure features a multi-institutional collaboration including hospitals, research laboratories, and universities. The infrastructure can provide students and researchers in biomedicine, mathematics, computer science, and engineering a platform for interaction and collaboration on development and use of computational techniques to model, process, quantify, and analyze various types of optical images. In addition the infrastructure offers training opportunities to students and early career researchers to apply their knowledge and skills in practice and to collaborate with investigators with different backgrounds.

与其他成像方式相比，光学成像在生物医学研究中越来越多地用于生物医学研究中的独特优势。光学成像涵盖了多个尺度，从使用生物发光和荧光的宏观成像，这些成像以毫米水平收集数据到2D和3D空间的微米水平的显微镜成像。结合高通量和染色技术，光学图像通常在多个通道上大量获取。结果，对于在生物医学研究中最大程度地使用的光学成像方法，光学成像的计算增强已成为数据管理和有效信息提取的必要性。该项目初始化并采用了一种多学科方法来计划创建社区基础设施计算增强的光学成像。计划阶段包括一个更大的研讨会和较小的目标会议，以及有关计算科学家，生物医学研究人员以及有关建立，功能，操作过程和用户​​访问计算增强的光学成像基础架构的访问的讨论。计划的社区基础设施具有多机构的合作，包括医院，研究实验室和大学。基础架构可以为生物医学，数学，计算机科学和工程学的学生和研究人员提供一个平台，用于开发和使用计算技术以建模，过程，量化和分析各种类型的光学图像。此外，基础设施为学生和早期职业研究人员提供了培训机会，以在实践中运用他们的知识和技能，并与背景不同的调查员合作。