Blender tissue cartography: an intuitive tool for the analysis of dynamic 3D microscopy data

Abstract

Tissue cartography extracts and cartographically projects surfaces from volumetric biological image data. This turns 3D- into 2D data which is much easier to visualize, analyze, and computationally process. Tissue cartography has proven particularly useful in developmental biology by taking advantage of the sheet-like organization of many biological tissues. However, existing software tools for tissue cartography are limited in the type of geometries they can handle or difficult for non-experts to use and extend. Here, we describe blender tissue cartography (btc), a tissue cartography add-on for the popular 3D creation software Blender. btc makes tissue cartography user-friendly via a graphical user interface and harnesses powerful algorithms from the computer graphics community for biological image analysis. The btc GUI enables interactive analysis and visualization without requiring any programming expertise, while an accompanying Python library allows expert users to create custom analysis pipelines. Both the add-on and the Python library are highly modular and fully documented, including interactive Jupyter Notebook tutorials. btc features a general-purpose pipeline for time-lapse data in which the user graphically defines a cartographic projection for a single key frame, which is propagated to all other frames via surface-to-surface alignment algorithms. The btc differential geometry module allows mathematically correcting for cartographic distortion, enabling faithful 3D measurements in 2D cartographic projections, including for vector fields like tissue flow fields. We demonstrate btc on diverse and complex tissue shapes from Drosophila, stem-cell-based organoids, Arabidopsis, and zebrafish.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

* https://github.com/nikolas-claussen/blender-tissue-cartography