Fluorender: An Imaging Tool for Visualization and Analysis of Confocal Data as Ap

Fluorender：用于共焦数据可视化和分析的成像工具

• 批准号: 8477216
• 负责人: Charles Hansen
• 金额: $ 30.2万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-20 至 2015-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8477216
• 关键词: 4D Imaging; Animals; Atlases; Automation; Axon; Biological Models; Cell Nucleus; Cells; Cellular Structures; Color; Communities; Computer software; Confocal Microscopy; Data; Data Set; Defect; Dendrites; Detection; Development; Disease; Disease model; Embryo; Excision; Fertilization; Four-dimensional; Genes; Genetic Techniques; Goals; Hand; Human; Image; Image Analysis; Imagery; Imaging Device; Imaging Techniques; Individual; Knock-out; Label; Larva; Length; Life; Location; Maps; Measures; Metabolic Diseases; Methods; Metric; Microscope; Mitosis; Modeling; Motion; Movement; Nervous system structure; Neurobiology; Neurologic; Optics; Organ; Phenotype; Physiological; Physiology; Positioning Attribute; Sampling; Scanning; Seeds; Shapes; Snakes; Specimen; Speed; Staining and Labeling; Structure; System; Techniques; Three-Dimensional Image; Three-dimensional analysis; Time; Tissues; Validation; Work; Zebrafish; analytical tool; base; cell motility; cellular imaging; commercial application; cost; fluorophore; human disease; improved; in vivo; interest; mutant; neuronal circuitry; phenome; research study; software development; tool

DESCRIPTION (provided by applicant): The zebrafish offers unique advantages as a vertebrate system to analyze cell and tissue structure and development in vivo. External fertilization and transparent larvae allow imaging of cells in live, developing animals. New genetic techniques can knock out most zebrafish genes, making it critical to develop high- throughput techniques to analyze mutant phenotypes (the "phenome project"). For all these experiments, confocal microscopy is an essential tool, making it equally critical to develop software to analyze 3D and 4D (3D over time) confocal data and quickly derive biologically-relevant conclusions, both qualitative and quantitative. Image analysis requires five steps: preprocessing, registration, visualization, segmentation, and quantitation. We have already developed a downloadable confocal analysis application, FluoRender, and optimized it for visualization, providing significant advantages over existing commercial applications. The present proposal would make FluoRender a full-featured package by adding the other four steps. Our goal is to enable the biologist to easily analyze 3D and 4D confocal data, identifying and measuring features of interest, and allowing rapid repetitive analysis of multiple samples. For features like segmentation that benefit from automation, we provide user validation and editing, emphasizing high accuracy rather than pure speed. We will focus on three specific problems: 1) 3D image mosaicking, 4D drift removal; 2) 3D segmentation of confocal data; and 3) 4D tracking in confocal data. Mosaicking allows scanning of specimens larger than a microscope's field of view. Timelapse experiments benefit from 4D drift removal, since the growing embryo can change shape or the microscope's focus can drift. We will develop segmentation methods for objects from three classes: nuclei/cells, axons/dendrites, and tissues. We will develop semi-automatic segmentation methods for zebrafish labeled with multiple fluorophores, or spectrally (Brainbow). We will develop methods so that once cells or tissues are initially segmented, they can be tracked over time, then visualized co-registered with the raw data, providing context for interpreting their motion. The improved FluoRender software will provide a freely-distributed, portable suite that enables rapid analysis of 3D or 4D confocal datasets. This will aid in analyzing cell movements, neuronal circuitry, and tissue development in wildtype and mutant embryos. Given the growing relevance of zebrafish as a human disease model, the proposed analysis software can be expected to benefit our understanding of many different developmental, neurobiological, and metabolic diseases.

描述（由申请人提供）：斑马鱼作为一种脊椎动物系统，在体内分析细胞和组织结构和发育具有独特的优势。体外受精和透明的幼虫使活的、发育中的动物细胞成像成为可能。新的基因技术可以敲除大多数斑马鱼基因，这使得开发高通量技术来分析突变表型（“表型计划”）变得至关重要。对于所有这些实验，共聚焦显微镜是必不可少的工具，因此开发软件来分析3D和4D（随时间推移的3D）共聚焦数据并快速得出定性和定量的生物学相关结论同样至关重要。图像分析需要五个步骤：预处理、配准、可视化、分割和定量。我们已经开发了一个可下载的共聚焦分析应用程序FluoRender，并对其进行了可视化优化，比现有的商业应用程序提供了显著的优势。目前的提案将通过添加其他四个步骤使FluoRender成为一个功能齐全的包。我们的目标是使生物学家能够轻松分析3D和4D共聚焦数据，识别和测量感兴趣的特征，并允许对多个样品进行快速重复分析。对于像分割这样得益于自动化的功能，我们提供用户验证和编辑，强调高精度而不是纯粹的速度。我们将重点关注三个具体问题：1)3D图像拼接，4D漂移去除；2)共聚焦数据的三维分割；3)共聚焦数据的四维跟踪。镶嵌技术可以扫描比显微镜视野更大的标本。延时实验得益于四维漂移去除，因为生长中的胚胎可以改变形状或显微镜的焦点可以漂移。我们将开发来自三类对象的分割方法：核/细胞、轴突/树突和组织。我们将开发半自动分割方法标记斑马鱼多荧光团，或光谱（Brainbow）。我们将开发方法，以便一旦细胞或组织最初被分割，它们就可以随着时间的推移而被跟踪，然后与原始数据进行可视化共同注册，为解释它们的运动提供上下文。改进的FluoRender软件将提供一个自由分布的便携套件，可以快速分析3D或4D共聚焦数据集。这将有助于分析野生型和突变型胚胎的细胞运动、神经回路和组织发育。鉴于斑马鱼作为人类疾病模型的相关性越来越大，所提出的分析软件可以使我们对许多不同的发育、神经生物学和代谢疾病的理解受益。