scenery: Flexible Virtual Reality Visualization on the Java VM

Abstract

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 from analysis of such data or simulations. Visualization is often the first step in making sense of data, and a crucial part of building and debugging analysis pipelines. It is therefore important that visualizations 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 visualization framework for the Java VM that can handle mesh and 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 example applications, such as its use in VR for microscopy, in the biomedical image analysis software Fiji, or for visualising agent-based simulations.

SNT: A Unifying Toolbox for Quantification of Neuronal Anatomy

“…Discrete graphics card is recommended for sciview integration. VR support in sciview requires the OpenVR/SteamVR library 4 .…”

“…S1a, S4a). For rendering more complex 3D data, SNT features two additional viewers: Reconstruction Viewer and sciview 4 integration.…”

“…For visualization, SNT features an interactive 3D viewer dedicated to neuron morphology -Reconstruction Viewer-that is hardware accelerated, supports rendering of meshes and detailed annotation of morphometry data. In addition, SNT also integrates with sciview 4 , a visualization tool for mesh-based data and arbitrarily large image volumes, supporting virtual, and augmented reality (Sup. Information).…”

“…SNT can run in headless environments, is fully scriptable and itself extensible. It inter-operates with other core components of the ImageJ ecosystem namely Sholl Analysis 10 , TrakEM229 , IJ ops30 , and scenery4 . SNT functionality can be extended using ImageJ2 commands6 or executable scripts, allowing both experienced developers and scientists with beginner-level programming experience to customize SNT.…”

An Architecture for Interactive In Situ Visualization and its Transparent Implementation in OpenFPM

“…For rendering images of simulation data, the rendering processes launch an application written using the open-source rendering library scenery [12]. Scenery uses the high-performance, low-level Vulkan API instead of OpenGL, as still predominantly used in most in situ tools, to better leverage the power of modern GPUs.…”