ArticlebioRxiv : the preprint server for biology2025
Blender tissue cartography: an intuitive tool for the analysis of dynamic 3D microscopy data.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Understanding complex, three-dimensional tissues requires volumetric microscopy, but visualization, analysis, and processing of 3D image data can be challenging. Tissue cartography is an emerging method that exploits the sheet-like organization of many biological tissues. Extracting and cartographically projecting curved surfaces from volumetric image data turns 3D into 2D data, which is much easier to visualize, analyze, and computationally process. However, existing tissue cartography tools both require advanced coding expertise and are limited to specific tissue geometries. Here, we create an interactive, visual tool for tissue cartography within Blender, a popular 3D animation environment. blender_tissue_cartography (btc), opens tissue cartography to broad use via a user-friendly graphical interface, while harnessing powerful computer graphics algorithms to process a wide variety of biological shapes. An accompanying Python library allows faithful 3D measurements in 2D cartographic projections and the creation of custom analysis pipelines. btc batch-processes time-lapse data by propagating a cartographic projection from a single
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.