Life science today involves computational analysis of a large amount and variety of data, such as volumetric data acquired by state-of-the-art microscopes, or mesh data resulting from analysis of such data or simulations. Visualisation is often the first step in making sense of the data, and a crucial part of building and debugging analysis pipelines. It is therefore important that visualisations can be quickly prototyped, as well as developed or embedded into full applications. In order to better judge spatiotemporal relationships, immersive hardware, such as Virtual or Augmented Reality (VR/AR) headsets and associated controllers are becoming invaluable tools. In this work we introduce scenery, a flexible VR/AR visualisation framework for the Java VM that can handle mesh and arbitrarily large volumetric data, containing multiple views, timepoints, and color channels. scenery is free and open-source software, works on all major platforms and uses the Vulkan or OpenGL rendering APIs. We introduce scenery's main features and detail example applications, such as its use in the biomedical image analysis software Fiji, or for visualising agent-based simulations.
翻译:今天的生命科学涉及对大量和多种数据进行计算分析,如通过最先进的显微镜获得的体积数据,或通过分析这些数据或模拟而获得的网状数据。视觉化往往是使数据具有意义的第一步,也是建设和调试分析管道的关键部分。因此,视觉化必须能够迅速进行原型,以及开发或嵌入到全部应用中。为了更好地判断时空关系,隐性硬件,例如虚拟或增强现实(VR/AR)头饰和相关控制器等,正在成为宝贵的工具。在这项工作中,我们引入了场景,一个灵活的VR/AR可视化框架,用于爪哇VM,可以处理网状和任意的大型体积数据,包含多个视图、时间点和颜色通道。景色是免费和开源软件,在所有主要平台上工作,并使用Vulkan或OpenGL 生成 APIs。我们引入了现场主要特征和详细示例应用,例如用于生物物理图像模拟软件斐济或视觉代理器。