Summary: Advances in 3D live cell microscopy are enabling high-resolution capture of previously unobserved processes. Unleashing the power of modern machine learning methods to fully benefit from these technologies is, however, frustrated by the difficulty of manually annotating 3D training data. MiCellAnnGELo virtual reality software offers an immersive environment for viewing and interacting with 4D microscopy data, including efficient tools for annotation. We present tools for labelling cell surfaces with a wide range of applications, including cell motility, endocytosis, and intracellular signalling. Availability and implementation: MiCellAnnGELo employs the cross platform (Mac/Unix/Windows) Unity game engine and is available under the MIT licence at https://github.com/CellDynamics/MiCellAnnGELo.git, together with sample data. MiCellAnnGELo can be run in desktop mode on a 2D screen or in 3D using a standard VR headset with compatible GPU.
翻译:概要: 3D活细胞显微镜的进展使得能够高清晰地捕捉以前未观察到的工艺。 释放现代机器学习方法的力量以充分受益于这些技术,但因难以人工说明3D培训数据而受挫。 MiCellAnnGELO虚拟现实软件为查看4D显微镜数据并与之互动提供了一个隐蔽的环境,包括有效的注解工具。 我们为细胞表面贴标签提供了各种应用工具,包括细胞运动、内分泌和细胞内信号。 可用性和实施: MiCellAnnGELO使用交叉平台(Mac/Unix/Windows)团结游戏引擎,可在麻省理工学院许可下,https://github.com/CellDynamics/MicellAnnGELo.git以及样本数据一起查阅。 MiCellAnnGELO可以在2D屏幕上或者在3D使用标准VR头与兼容的GPU进行桌面操作。