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Pathtrace rendering of 3D cells

Visualization Advances for Enhancing Spatial Relationships
Introducing AGAVE

β-testing code-name for the Advanced GPU Accelerated Volume Explorer
 
Download AGAVE from the Software page
Available for Windows & MacOS

What's New

November 12, 2020
  • scene selection dialog when opening multiscene files
  • added support for loading files with 8-bit intensities
  • new documentation
  • updated Qt to 5.15 LTS
  • minor bug fixes with JSON save and load
  • improved logging

Archived

Download AGAVE for Mac 0.9.0.0
Download AGAVE for Windows 0.9.0.0

What's New

March 30, 2020
  • Transfer function editor
  • Time series support (loads one time sample at a time)
  • Embedded Python and Python script export
  • Miscellaneous UI improvements
  • Zeiss CZI file support​

Try a simpler viewer in your browser

Picture
Cell Feature Explorer with pathtrace
Visit the Cell Feature Explorer, click on any dot in the plot to load a cell into the gallery. Click on any cell in the gallery to load it into the online 3D volume viewer at the bottom of the page. Unfold [>Global volume rendering settings] and [√] the Path trace button at the bottom. Turn on all Volumes in the Segmentation channels and turn off all volumes in the Observed channels as a starting point. Adjust the transfer function graphs to find an ideal setting.

Try the full viewer on your desktop

Picture
Software Download page
The AGAVE viewer is available for Mac and Windows operating systems, and can be built from source for Linux. AGAVE uses path-trace rendering in an interface designed and optimized for the display of multi-channel OME TIFF files.

For this v1.0 release, we provide documentation for using AGAVE to help you explore its capabilities. 

Archived

This beta release of the AGAVE viewer is available for Mac and Windows operating systems. The volume viewer used path-trace rendering in an interface designed and optimized for the display of multi-channel, single-time OME TIFF files.

After the v1.0 release, we will provide tutorials for using AGAVE, but the current distribution offers a readme file to help you explore preview of the capabilities.

Visualization Advances for Enhancing Spatial Relationships… Even Online

Most volumetric visualization tools that cell biologists use have evolved from 2D image analysis predecessors. They provide powerful analysis capabilities, especially for looking at one slice of a 3D volume or a projection, but they have limited 3D visualization functionality. Transforming a stack of 2D slices into a 3D volume and then interactively rotating it makes complex spatial relationships easier to see and understand.

The most common 3D volume rendering methods make the stacked image slices transparent so the observer can see through the entire volume. However, this can compromise the appearance and detail of the signal (Fig. 1A). Users can adjust the transparency to make denser voxels (the 3D analog to pixels) stand out, but this rendering approach is far removed from how we view and intuitively interact with everyday objects, lacking, for example, any concept of a directional light source, adjustable highlights, or shadows that can help us intuit complex topologies and distance relationships. The volumes can require longer interactions and more experience to interpret, and it can be impossible to correctly interpret depth relationships if the user cannot interactively rotate the volume, for example if it is displayed on a printed page.

New approaches to rendering volumes are being adapted and developed for use in cell biology to help us literally see the cells in a more familiar and thus intuitive manner. For example, by adopting approaches such as “cinematic rendering” techniques to cellular volumetric data, one can see fine details become more visible and spatial relationships more interpretable, even in a 2D static printed image (Fig. 1B). This makes exploring cellular data more analogous to dissecting a cadaver rather than looking only at x-ray projections when learning human anatomy. These types of approaches should become an important addition to the arsenal of visual analysis tools needed to study and see a cell from every possible perspective and in every possible way. This cinematic approach can also be adjusted to emulate the method shown in (a) when transparency is useful.
Picture
Figure 1: Live hiPS cells in a monolayer are labeled for the cell boundary (magenta), DNA (cyan), and microtubules (white). Cells are imaged in 3D using spinning disk confocal microscopy and the image is displayed with: a) the most common type of volume rendering method as in this example from www.allencell.org/3d-cell-viewer.html; and b) newly adopted “cinematic lighting” techniques to volume rendering in development at the Allen Institute for Cell Science. 

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  • About
    • What We Do
    • FAQs
    • Videos & Tutorials
    • Site Updates
    • < Forum >
    • < AllenInstitute.org >
  • Animated Cell
    • Educational Resources
    • Visual Guide to Human Cells
    • Visual Guide Tutorial
    • Research Projects >
      • Pathtrace rendering
  • Cells & Biology
    • Cell Catalog
    • About our Cells >
      • hiPS Cell Biology Overview
      • Cell Structure Observations
      • Cell Catalog QuickView
    • Genomics
    • Methods & SOPs >
      • Methods for Cells in the Lab
      • Cell Methods: Videos from the Lab
      • Methods for Microscopy
    • Research Projects >
      • hiPS Cells During Mitosis
      • Drug Perturbation Pilot
      • Differentiation Into Cardiomyocytes
      • Why Endogenous Tagging?
  • Data & Tools
    • Cell Catalog
    • 3D Cell Viewer
    • Cell Feature Explorer
    • Integrated Mitotic Stem Cell Z-stack Viewer
    • Deep Cell Zoom
    • Segmenter
    • Data Downloading
    • Software & Code
    • Simularium
    • Research Projects >
      • Extracting Information
  • Modeling & Analysis
    • Integrated Mitotic Stem Cell
    • Allen Integrated Cell
    • Label-free Determination
    • Data Notebook Exploration >
      • Cell Shape Analysis
      • Programmatic Data Access
    • Research Projects >
      • 3D Probabilistic Modeling
  • News & Publications
    • News Feed
    • Publications
    • Archived Content