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Published on: October 28, 2018
Spherical Harmonics based extraction and annotation of cell shape in 3D time-lapse microscopy sequences
Christel Ducroz1, Jean-Christophe Olivo-Marin, Alexandre Dufour
1Institut Pasteur, Quantitative Image Analysis Unit, 25 rue du Dr Roux, F-75015 Paris, France. fcducroz@pasteur.fr
Summary
This study introduces a new framework using Spherical Harmonics (SPHARM) to classify cell shapes from 3D time-lapse images. This method accurately quantifies cell deformation and aids in automated analysis of cell populations.
Area of Science:
- Cell Biology
- Biophysics
- Image Analysis
Background:
- Cell deformation and motility are crucial in life sciences.
- Accurate cell shape quantification is needed for analysis and classification.
- High cell shape variability within populations presents a challenge.
Purpose of the Study:
- To develop a framework for cell shape extraction and classification in 3D time-lapse sequences.
- To address the challenge of cell shape variability.
- To enable automated analysis and comparison of cell populations.
Main Methods:
- Utilized the Spherical Harmonics (SPHARM) transform for surface representation.
- Employed unsupervised multi-class K-Means clustering for classification.
- Applied the framework to 3D time-lapse sequences of living cells.
Main Results:
- Represented cell surfaces with unique SPHARM coefficients, invariant to translation and orientation.
- Successfully classified different phases of cell deformation.
- Demonstrated automated sequence annotation capabilities.
Conclusions:
- The proposed SPHARM-based framework provides robust cell shape extraction and classification.
- The method facilitates automated annotation and comparison of cell shape characteristics.
- This approach is valuable for studying cell dynamics and population differences.
