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

Abstract

Volumetric microscopy can image complex 3D tissues, but 3D image data remains difficult to visualize and quantify. Many biological systems are organized as thin, curved sheets (for example, epithelia). Tissue cartography extracts and cartographically projects these curved surfaces from volumetric images. This converts 3D into 2D image data, greatly facilitating visualization, analysis, and computational processing. Existing tools, however, demand advanced coding expertise and are limited to simple tissue geometries. Here, we present blender issue cartography (btc), an interactive add-on for the 3D editor Blender that makes tissue cartography user-friendly by a graphical interface, and handles complex biological shapes using powerful computer graphics algorithms. An accompanying Python library supports faithful 3D measurements in 2D cartographic projections and custom analysis pipelines. Time-lapse data can be batch-processed by algorithmically aligning all time points to a single key frame. We demonstrate btc on diverse and complex tissue shapes from Drosophila, stem-cell organoids, Arabidopsis, and zebrafish. btc enables quantitative cartographic analysis of complex 3D tissues, broadening access to methods previously restricted to specialists, while leveraging tools from computer graphics to unlock new capabilities.