Center for Open Bioimage Analysis

开放生物图像分析中心

• 批准号: 10378104
• 负责人: Anne E. Carpenter
• 金额: $ 35.84万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10378104
• 关键词: Active Learning; Address; Algorithms; Area; Automobile Driving; Benchmarking; Biological; Biological Models; Biological Process; Biology; Biomedical Research; Cell Nucleus; Cells; Cellular Structures; Cellular biology; Communities; Complement; Complex; Computational Technique; Computer Vision Systems; Computer software; Computers; Data; Data Set; Development; Dimensions; Disease; Ensure; Event; Face; Feedback; Future; Image; Image Analysis; Institutes; International; Laboratories; Letters; Machine Learning; Measures; Methods; Microscopy; Mission; Modality; Modeling; Online Systems; Organism; Phenotype; Process; Reproducibility; Research; Research Personnel; Resource Sharing; Resources; Risk; Role; Scientist; Side; Software Engineering; Software Tools; Structure; Techniques; Technology; Time; Tissues; Training; Translating; Universities; Validation; Variant; Wisconsin; Work; advanced analytics; base; bioimaging; biological research; catalyst; deep learning; deep learning model; deep neural network; diagnostic tool; experience; experimental study; graphical user interface; image processing; imaging modality; improved; innovation; interest; learning strategy; light microscopy; machine learning method; microscopic imaging; neural network; next generation; open source; quantitative imaging; research and development; scale up; skills; software development; technology research and development; tool; user friendly software; user-friendly

Project Summary The Center for Open Bioimage Analysis will serve the cell biology community’s growing need for sophisticated software for light microscopy image analysis. Quantitative image analysis has become an indispensable tool for biologists using microscopy throughout basic biological and biomedical research. Quantifying images is now a critical, widespread need as imaging experiments continue to grow in scale, size, dimensionality, scope, modality, and complexity. Many biologists are missing out on the quantitative bioimaging revolution due to lack of effective algorithms and/or usable software for their needs, or lack of access to training. The Center brings together the Carpenter laboratory at the Broad Institute and the Eliceiri laboratory at the University of Wisconsin­Madison, and in doing so brings together the two most popular open source bioimage analysis projects, ImageJ (including ImageJ2 and FIJI) and CellProfiler. Through the collaborative development and dissemination of open source image analysis software, as well as training events and resources, the Center will empower thousands of researchers to apply advanced analytics in innovative ways to address new experimental areas. Building on the team’s expertise developing algorithms and user­friendly software for use in biology under real­world conditions, the Center will focus on two Technology Research and Development (TR&D) projects: deep learning­based image processing, and accessibility of image­processing algorithms for biologists. This work will not occur in isolation at the Center; rather, the Center will nucleate a larger community working on these two areas and serve as a catalyst and organizing force to create software and resources shared by all. The Driving Biological Projects (DBPs) will serve a major role in driving the TR&D work: our teams are accustomed to working deeply and iteratively on problems side by side and with frequent feedback from biologists. This will ensure that important cell biological problems drive the work of the Center. The DBPs reflect tremendous variety in terms of biological questions, model systems, imaging modalities, and researcher expertise and will ensure robustness of our tools for the widest possible impact on the community. Continuing the teams’ track record with ImageJ and CellProfiler, two mature open source bioimage analysis software projects critical to the work of biologists worldwide, the Center will also assist and train biologists in applying the latest computational techniques to important biological problems involving images. In short, the need for robust, accurate, and readily usable software is more urgent than ever. The Center for Open Bioimage Analysis will serve as a hub for pioneering new computational strategies for diverse biological problems, translating them into user­friendly software, further developing ImageJ and CellProfiler, and training the biological community to apply advanced software to important and diverse problems in cell biology.

项目摘要 开放生物图像分析的中心将满足细胞生物学社区日益增长的需求 用于光学显微镜图像分析的软化软件。定量图像分析已成为 通过基本的生物学和生物医学研究使用显微镜的生物学家必不可少的工具。 量化图像现在是一个关键的，宽度的需求，因为成像实验的规模继续增长， 大小，维度，范围，方式和复杂性。许多生物学家错过了定量 由于缺乏有效的算法和/或可用的软件来满足其需求，或者缺乏生物成像革命 进入培训。该中心汇集了布罗德学院和Eliceiri的木匠实验室 威斯康星大学的实验室，这样做的两个最受欢迎的公开 源生物图像分析项目，ImageJ（包括ImageJ2和Fiji）和CellProfiler。通过 开源图像分析软件的协作开发和传播以及培训 活动和资源，该中心将授权成千上万的研究人员在 解决新实验领域的创新方法。 建立在团队的专业知识的基础上开发算法和用户友好的软件，用于生物学 现实世界的条件，该中心将专注于两个技术研发（TR＆D）项目： 基于深度学习的图像处理以及生物学家图像处理算法的可访问性。这 中心不会孤立地进行工作；相反，该中心将核对一个更大的社区核心 这两个领域，并充当催化剂和组织力量，以创建所有人共享的软件和资源。 驾驶生物项目（DBP）将在驱动TR＆D工作中发挥重要作用：我们的团队是 习惯于并排进行深入和迭代的工作，并经常出现在 生物学家。这将确保重要的细胞生物学问题推动中心的工作。 DBP 在生物问题，模型系统，成像方式和研究人员方面反映了巨大的多样性 专业知识，并将确保我们的工具的鲁棒性，从而对社区产生最广泛的影响。继续 团队通过ImageJ和Cellprofiler的往绩记录，两个成熟的开源生物图像分析软件 对全球生物学家工作至关重要的项目，该中心还将协助和培训生物学家申请 重要生物问题的最新计算技术涉及图像。 简而言之，对强大，准确且易于使用的软件的需求比以往任何时候都更加紧迫。中心 开放的生物图像分析将成为领导潜水员生物学新计算策略的枢纽 问题，将它们转化为用户友好的软件，进一步开发ImageJ和CellProfiler以及培训 生物界将高级软件应用于细胞生物学的重要和潜水问题。