https://github.com/aafkegros/MicroscopyNodes
Loading and handling microscopy data in blender
https://github.com/aafkegros/MicroscopyNodes
blender blender-addon microscopy volume-rendering
Last synced: 8 months ago
JSON representation
Loading and handling microscopy data in blender
- Host: GitHub
- URL: https://github.com/aafkegros/MicroscopyNodes
- Owner: oanegros
- License: gpl-3.0
- Created: 2023-10-03T14:19:28.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-01-23T08:54:39.000Z (over 1 year ago)
- Last Synced: 2025-01-23T09:33:33.754Z (over 1 year ago)
- Topics: blender, blender-addon, microscopy, volume-rendering
- Language: Python
- Homepage: https://oanegros.github.io/MicroscopyNodes/
- Size: 491 MB
- Stars: 108
- Watchers: 5
- Forks: 8
- Open Issues: 18
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-scientific-image-analysis - tif2blender
README
# 
Microscopy in Blender
**Microscopy Nodes** is a Blender add-on for visualizing high-dimensional microscopy data—designed for scientists, or anyone working with biological images 😊.
For any type of microscopy: fluorescence, electron microscopy, or anything in between! This tool helps you turn complex 3D+ datasets into stunning, accurate, and animatable visualizations.
Usage questions are mainly answered on the [image.sc forum](https://forum.image.sc/tag/microscopy-nodes)
## 
What It Does
Microscopy Nodes supports importing **up to 5D** microscopy datasets (XYZ + time + channels) from `.tif` and **OME-Zarr** files, setting easy and adaptable settings to start with visualizing your data.
| Feature | Description |
|--------|-------------|
| **5D Support** | Load `.tif` and `.zarr` files with any axis order 'tzcyx' or any subset |
| **Channel Interface** | Define how to load each channel: 
volume, 
surface, 
label mask |
| **Colors and LUTs** | Easy picking of colors per channel or non-linear LUT selection from [many colormaps](https://cmap-docs.readthedocs.io/en/stable/). |
| **Intuitive Slicing** | Slice any object by moving the Slicing Cube, as you would move any other Blender object |
| **Scales** | 3D scale grid for accurate representation and physical Blender scales for easy registration. |
| **Large Volumes** | Build your animation and visualization on a downscaled version, render with your massive dataset! |
## 
Installation
You can grab the add-on on the [Blender Extensions Platform](https://extensions.blender.org/add-ons/microscopynodes/)
Or, search **Microscopy Nodes** in Blender Preferences → Get Extensions. (Blender 4.2+)
For earlier versions, check the [legacy install guide](https://aafkegros.github.io/MicroscopyNodes/outdated).
Once installed, find it under Scene Properties 
.
## 
Video tutorials
Check out the [video tutorials](https://www.youtube.com/@aafkegros) on YouTube for quick guides on:
- Installation
- Loading data
- Fluorescence & EM visualization
- Making presentation-ready renders
## First use
1. Load your file (local path or URL) into the **Microscopy Nodes** panel in Scene Properties
2. The metadata will auto-load, and you can define how each channel is visualized
3. Adjust per-channel options like:
- Volume or isosurface rendering
- Label masks
- Emission, resolution, and colors
4. Customize dataset settings like:
- Axis order
- Physical pixel size
- Reload behavior & storage location
More detail in the [full docs](https://aafkegros.github.io/MicroscopyNodes/).
## Show Off Your Vizualizations!
If you create something cool using `Microscopy Nodes`, share it!
Tag me [@aafkegros on Bluesky](https://bsky.app/profile/aafkegros.bsky.social) or use the hashtag `#microscopynodes`.
If you publish with this add-on, please cite [the preprint](https://www.biorxiv.org/content/10.1101/2025.01.09.632153v1):
```
@article {Gros2025.01.09.632153,
author = {Gros, Oane and Bhickta, Chandni and Lokaj, Granita and Schwab, Yannick and K{\"o}hler, Simone and Banterle, Niccol{\`o}},
title = {Microscopy Nodes: versatile 3D microscopy visualization with Blender},
elocation-id = {2025.01.09.632153},
year = {2025},
doi = {10.1101/2025.01.09.632153},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2025/01/14/2025.01.09.632153},
eprint = {https://www.biorxiv.org/content/early/2025/01/14/2025.01.09.632153.full.pdf},
journal = {bioRxiv}
}
```