CAREER: Image information extraction from heterogeneous populations of co-cultured cells

布罗德研究所获得了一个奖项，以确定和验证自动图像分析方法，从共培养细胞系统的荧光显微镜图像中提取信息，同时教育学生、科学家和公众关于生物图像分析的理论、实践和社会影响。生物学家越来越多地使用共培养系统，其中两种或两种以上的细胞类型一起生长，以便更准确地模拟其原生环境。为了利用这些强大的共培养系统来解决广泛的基础生物学研究问题，剩下的挑战是在这种共培养的显微镜图像中准确地提取每个细胞的定量测量，因为存在不同形态的细胞类型。与使用共培养系统的研究人员密切合作，并在PI？作为在生物图像分析方面的成功工作，CAREER项目将图像分析研究与教学相结合。该项目将为科学界提供一个经过验证的开源软件工具箱，其中包含图像处理和机器学习算法，生物学家可以随时使用。该项目的教育和推广工作将产生经过验证的、引人入胜的教育材料，供世界各地的高中教师自由使用。有关该项目的更多信息可以在http://www.broadinstitute.org/~anne/Carpenter_NSF_CAREER.html上找到

An award is made to the Broad Institute to identify and validate automated image analysis approaches to extract information from fluorescence microscopy images of co-cultured cell systems, while educating students, scientists, and the public about the theory, practice, and societal impact of biological image analysis. Biologists increasingly use co-culture systems, where two or more cell types are grown together in order to more accurately model their native environment. In order to use these powerful co-culture systems to tackle a wide range of basic biological research questions, the remaining challenge is to accurately extract quantitative measurements from each cell in microscopy images of such co-cultures, given that cell types with diverse morphologies are present. In close collaboration with researchers using co-culture systems, and building on the PI?s successful work in biological image analysis, this CAREER project integrates image analysis research and education. The project will give the scientific community a validated, open-source software toolbox of image processing and machine learning algorithms readily usable by biologists. The education and outreach efforts of the project will produce validated, engaging educational materials that can be freely implemented by high school teachers around the world. More information about the project can be found at: http://www.broadinstitute.org/~anne/Carpenter_NSF_CAREER.html