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Extracting multiple surfaces from 3D microscopy images in complex biological tissues with the Zellige software tool
Céline Trébeau1, Jacques Boutet de Monvel1, Gizem Altay1
1Institut Pasteur, Université Paris Cité, Inserm, Institut de l'Audition, F-75012, Paris, France.
BMC Biology
|August 23, 2022
Summary
Zellige software extracts multiple 2D surfaces from 3D microscopy images, even with complex topography or low contrast. This automated tool aids in studying cellular choreography during development and tissue interactions.
Area of Science:
- Cell Biology
- Developmental Biology
- Bioimaging
Background:
- Extracting 2D surfaces from 3D microscopy is crucial for understanding epithelium morphogenesis.
- Existing methods struggle with rough surfaces, low contrast, or overlapping structures.
- Manual segmentation for multiple surfaces is time-consuming and labor-intensive.
Purpose of the Study:
- To develop an automated tool for extracting multiple 2D surfaces from 3D microscopy data.
- To overcome limitations of existing methods in handling complex biological structures.
- To facilitate studies of tissue-tissue and tissue-matrix interactions.
Main Methods:
- Developed Zellige software, a Fiji plugin for 3D image analysis.
- Implemented an intuitive interface with adjustable control parameters.
- Designed to extract a variable number of surfaces with diverse characteristics.
Main Results:
- Zellige successfully extracts multiple surfaces regardless of inclination, contrast, or texture.
- The software automates segmentation, reducing manual annotation efforts.
- Demonstrated robustness on synthetic data and diverse biological samples.
Conclusions:
- Zellige provides a versatile and efficient solution for 2D surface extraction from 3D microscopy.
- The tool enhances the study of complex cellular processes and tissue interactions.
- Automated segmentation with Zellige accelerates research in developmental biology and bioimaging.
