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、分辨率和通用性等方面具有独特的优势，在生物医学研究中得到了越来越广泛的应用。光学成像跨越多个尺度，从使用生物发光和荧光收集毫米级数据的宏观成像，到二维和三维空间微米级的微观成像。结合高通量和染色技术，光学图像通常会在几个通道上大量获取。因此，为了在生物医学研究中最大限度地使用光学成像方法，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。该项目初始化并采用多学科方法来规划创建用于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，以及征求计算科学家、生物医学研究人员和工程师对计算增强型光学成像基础设施的建立、功能、操作过程和用户访问的意见的讨论。规划中的社区基础设施以多机构合作为特色，包括医院、研究实验室和大学。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在开发和使用计算技术来对各种类型的光学图像进行建模、处理、量化和分析方面进行交互和协作的平台。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，以便将他们的知识和技能应用于实践，并与具有不同背景的调查人员合作。

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.