ArticleFrontiers in physiology2016
Limits of Applicability of the Voronoi Tessellation Determined by Centers of Cell Nuclei to Epithelium Morphology.
Article in Frontiers in physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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23 citing papers in PubMed.
- Multicellular simulations with shape and volume constraints using optimal transport.Science advances · 2026Article
- PhenoBIC: operator-free single-cell spatial phenotyping in multiplex imaging data using deep learning of cell staining patterns.bioRxiv : the preprint server for biology · 2026Article
- Stereological reconstructions of 3D cellular microstructures by combining adversarial learning and Voronoi tessellations.Scientific reports · 2026Article
- Gap Junctional Versus Paracrine Signaling in the Human Lens Epithelium: Analysis Based on Multicellular Ca²⁺ Imaging and Computational Modeling.Investigative ophthalmology & visual science · 2025Article
- Evaluating segmentation methods for UAV-Based Spoil Pile Delineation.Scientific reports · 2025Article
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- Capturing the mechanosensitivity of cell proliferation in models of epithelium.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Two conjectures on 3D Voronoi structures: a toolkit with biomedical case studies.Molecular systems design & engineering · 2024Article
- ConfluentFUCCI for fully-automated analysis of cell-cycle progression in a highly dense collective of migrating cells.PloS one · 2024Article
- CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia.Cell reports methods · 2023Article
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- MIRIAM: A machine and deep learning single-cell segmentation and quantification pipeline for multi-dimensional tissue images.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2022Article
- Delineating the mechanisms and design principles ofComputational and structural biotechnology journal · 2022Review
- Co-cultures of cerebellar slices from mice with differentF1000Research · 2022Article
- Combining experiments and in silico modeling to infer the role of adhesion and proliferation on the collective dynamics of cells.Scientific reports · 2021Article
- Mechanical feedback and robustness of apical constrictions in Drosophila embryo ventral furrow formation.PLoS computational biology · 2021Article
- The Voronoi theory of the normal liver lobular architecture and its applicability in hepatic zonation.Scientific reports · 2021Article
- Six-Color Confocal Immunofluorescence Microscopy with 4-Laser Lines.Methods in molecular biology (Clifton, N.J.) · 2021Article
- ACDC: Automated Cell Detection and Counting for Time-Lapse Fluorescence Microscopy.Applied sciences (Basel, Switzerland) · 2020Article
- Multiscale modelling of drug transport and metabolism in liver spheroids.Interface focus · 2020Article
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Abstract
It is well accepted that cells in the tissue can be regarded as tiles tessellating space. A number of approaches were developed to find an appropriate mathematical description of such cell tiling. A particularly useful approach is the so called Voronoi tessellation, built from centers of mass of the cell nuclei (CMVT), which is commonly used for estimating the morphology of cells in epithelial tissues. However, a study providing a statistically sound analysis of this method's accuracy is not available in the literature. We addressed this issue here by comparing a number of morphological measures of the cells, including area, perimeter, and elongation obtained from such a tessellation with identical measures extracted from direct imaging acquired by staining the cell membranes. After analyzing the shapes of 15,000 MDCK II epithelial cells under several conditions, we find that CMVT reasonably well reproduces many of the morphological properties of the tissue with an error that is between 10 and 15%. Moreover, cross-correlations between different morphological measures are reproduced qualitatively correctly by this method. However, all of the properties including the cell perimeters, number of neighbors, and anisotropy measures often suffer from systematic or size dependent errors. These discrepancies originate from the polygonal nature of the tessellation which sets the limits of the applicability of CMVT.
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