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 transmembrane 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 and demonstration movies. 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先前未观测到的工艺。 但是,由于难以手工说明3D培训数据,释放现代机器学习方法的力量以充分受益于这些技术而受挫。 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。我们提供了对细胞表面进行标签的工具,其应用范围很广,包括细胞运动、内分泌和感应信号。可用性和实施: MiCellAnnGELO使用十字平台(Mac/Unix/Windows)团结游戏引擎,根据麻省理工学院的许可证可在https://github.com/CellDynamics/MICellAnnGELO.git上查阅,同时提供样本数据和示范电影。 MiCellAnnGELO可以以桌面模式在2D屏幕上运行,或3D使用标准VR头与GPU运行。