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

与其他成像方式相比，光学成像在灵敏度、特异性、分辨率和多功能性方面具有独特的优势，因此越来越多地用于生物医学研究。光学成像跨越多个尺度，从使用生物发光和荧光的宏观成像（收集毫米级数据）到2D和3D空间中微米级的微观成像。结合高通量和染色技术，光学图像通常在多个通道上大量采集。因此，为了使光学成像方法在生物医学研究中得到最大限度的应用，光学成像的计算增强已经成为数据管理和有效信息提取的必要条件。本项目采用多学科方法，规划创建计算增强光学成像的社区基础设施。规划阶段包括一个较大的研讨会和较小的，有针对性的会议和讨论，以征求来自计算科学家，生物医学研究人员和工程师关于建立，功能，操作过程和用户访问的计算增强的光学成像基础设施的输入。计划中的社区基础设施包括医院、研究实验室和大学等多机构合作。该基础设施可以为生物医学，数学，计算机科学和工程领域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来建模，处理，量化和分析各种类型的光学图像。此外，该基础设施还为学生和早期职业研究人员提供培训机会，使他们能够在实践中应用自己的知识和技能，并与不同背景的研究人员合作。

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.