Imaging Management and Analysis Core

影像管理和分析核心

基本信息

批准号：
10166786
负责人：
JOE W. GRAY
金额：
$ 20.41万
依托单位：
OREGON HEALTH & SCIENCE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-05-01 至 2023-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10166786
关键词：
3-Dimensional Address Algorithmic Analysis Algorithms Architecture Back Biological Assay Biological Markers Cell Culture Techniques Cell Line Cells Cellular Morphology Characteristics Classification Collaborations Complex Computer Systems Computer software Custom Data Data Storage and Retrieval Databases Development Electron Microscope Electrons Environment Face Heterogeneity High Performance Computing Image Image Analysis Imaging Device Immunofluorescence Immunologic Individual Infrastructure Ingestion Label Light Microscope Link Machine Learning Measurement Measures Metadata Methods Microscopic Modeling Nature Performance Periodicity Pharmaceutical Preparations Phenotype Population Procedures Process Protocols documentation Qi Quality Control Resolution Resource Sharing Resources Scanning Electron Microscopy Selection Criteria Structure System Systems Biology Tissues Visualization Visualization software base cancer heterogeneity data management experimental study feature extraction flexibility fluorescence imaging high dimensionality image reconstruction imaging Segmentation imaging approach imaging system insight light microscopy multimodality novel open source outreach protocol development quality assurance quantitative imaging repository response screening segmentation algorithm tool

项目摘要

ABSTRACT – Imaging Management and Analysis Core The Imaging Management and Analysis Core (Imaging Core) will meet the requirements of the three Measuring, Modeling, and Controlling Heterogeneity-Cancer Systems Biology Consortium (M2CH-CSBC) Projects and the Outreach Core by developing and integrating state-of-the-art resources for a complete imaging workflow. Specifically, we will 1) use high-content imaging to measure baseline and drug and microenvironment response phenotypes separately and in combination in a panel of cell lines, 2) optimize and deploy novel, highly multiparameter cyclic multiplexed immunofluorescence (cmIF) imaging workflows to measure microenvironment and drug responses in heterogeneous tissues in 2D and 3D, and 3) deploy correlative light/electron microscopic analysis based on super-resolution light microscopy and scanning electron microscopy to provide the ultrastructural cellular context. To execute these tasks in close collaboration with the Projects, the Imaging Core will expand on existing resources and build a customized imaging environment to a) acquire image data in automated ways from the multiple imaging instruments, following precise protocols and maintaining complete metadata, b) store images and metadata and all derived and associated measurement data in highly robust databases and repositories with powerful query, visualization, and programmer access tools, c) quantitatively analyze images by deploying and developing state-of-the-art image reconstruction methods, image segmentation algorithms, feature extraction and classification routines, normalization procedures, and machine learning approaches to classify image features at multiple resolution levels, and d) develop novel visualization methods for interacting with images and extracted features and models in combination with experimental metadata and data from external databases.

摘要 - 成像管理和分析核心成像管理和分析核心（成像核心）将满足三个的要求测量，建模和控制异质性 - 癌性系统生物学联盟（M2CH-CSBC）通过开发和集成最先进的资源来完成项目和外展核心成像工作流程。特别是，我们将1）使用高含有成像来测量基线和药物以及微环境反应表型分别和组合组合中的细胞系组合，2）优化和优化部署新颖的高度多参数循环多路复用免疫荧光（CMIF）成像工作流程测量2D和3D中异质组织中的微环境和药物反应，以及3）部署基于超分辨率光显微镜和扫描的相关光/电子显微镜分析电子显微镜提供超微结构细胞环境。密切合作执行这些任务通过项目，成像核心将扩展现有资源并构建自定义成像环境a）从多个成像仪器中以自动方式获取图像数据，精确协议并维护完整的元数据，b）存储图像和元数据以及所有衍生具有强大查询，可视化，可视化的数据库和存储库中相关的测量数据和程序员访问工具，c）通过部署和开发最先进的方式定量分析图像图像重建方法，图像分割算法，特征提取和分类例程，标准化程序和机器学习方法以多分辨率对图像特征进行分类级别，d）开发新型的可视化方法，以与图像和提取的特征相互作用和模型与实验元数据和外部数据库的数据结合使用。