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filoVision - 使用深度学习和尖端标记器来自动化filopodia分析

Casey Eddington^1,2, Jessica K Schwartz¹, Margaret A Titus^1,2

¹Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, MN 55455, USA.

Journal of cell science

|January 24, 2024

概括

FiloVision是一个新的深度学习平台,可以自动化filopodia分析. 它提供了用于分析filopodia尖端和轴的工具,即使使用有限的标记器,也改善了细胞探索研究.

科学领域:

细胞生物学细胞生物学
生物技术是生物技术.
显微镜的使用方法

背景情况:

菲洛波迪亚是环境感应的关键细胞结构.
分析filopodia通常需要特定的标记物 (动蛋白,尖端或膜).
现有的方法对不同的细胞类型和可视化偏好构成挑战.

研究的目的:

开发一个自动化的filopodia分析工作流程.
为了解决只使用尖端标签分析阿米类类动物的需要.
为Filopodia研究创建一个灵活的深度学习平台.

主要方法:

开发 filoVision 深度学习平台.
实施 filoTips 用于标记 filopodia 尖端和细胞质.
整合 filoSkeleton 用于分析带有 actin 标记的 filopodia 轴.
使用ZeroCostDL4Mic框架来实现适应性.

主要成果:

FiloVision允许使用单一尖端标记器对filopodia进行自动分析.
FiloTips可以在没有actin或膜标记器的情况下进行信息提取.
FiloSkeleton提供了对filopodia轴和尖端蛋白质的全面分析.
该平台可适应各种细胞类型和用户数据集.

结论:

FiloVision提供了一种灵活和自动化的解决方案,用于filopodia分析.
该平台提高了研究研究细胞探索的研究人员的可访问性.
FiloVision支持filopodia研究中的多种可视化方法和细胞类型.

关键词:

计算机视觉计算机视觉计算机视觉深度学习是一种深度学习.菲洛波迪亚 (Filopodia) 是一种类动物.图像分析管道中的一个.这就是 filoVision 的意义.

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