ArticleCell reports methods2023
CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia.
Article in Cell reports methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 17 citations in OpenAlex.
- Organoid Intelligent Morphomics: Decoding the organoid morphome through artificial intelligence from phenotypic quantification to mechanistic insight.Bioactive materials · 2027Review
- The Interplay of Curvature, Geometry, and Topology Shapes Tissue Organisation in Epithelial Shells.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Review
- Automated segmentation of neurons and spinal cord structures in immunofluorescence images using SpineDL.Scientific reports · 2026Article
- The V-ATPase/ATG16L1 axis drives membrane remodeling during epithelial morphogenesis.Nature communications · 2026Article
- 3D epithelial cell topology tunes signaling range to promote precise patterning.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Experimental Tools and Techniques for Studying Microtubule Nucleation at the Centrosome and the Golgi Apparatus.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Article
- Spatiotemporal segmentation of contraction waves in the extra-embryonic membranes of the red flour beetle.BMC bioinformatics · 2025Article
- Review
- CellMet: Extracting 3D shape and topology metrics from confluent cells within tissues.PLoS computational biology · 2025Article
- Apico-basal intercalations enable the integrity of curved epithelia.Computational and structural biotechnology journal · 2025Article
- Local and global changes in cell density induce reorganisation of 3D packing in a proliferating epithelium.Development (Cambridge, England) · 2024Article
- Novel imaging and biophysical approaches to study tissue hydraulics in mammalian folliculogenesis.Biophysical reviews · 2024Review
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Authors and funding
15 authors at 8 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.
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