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Updated: May 26, 2025

Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans

Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans

Published on: July 5, 2019

Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour.

Dominik Schienstock¹, Jyh Liang Hor^1,2, Sapna Devi¹

¹Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia.

Nature Communications

|February 24, 2025

Summary

This summary is machine-generated.

Cecelia is a new toolbox that simplifies quantitative image analysis for researchers. It integrates open-source tools for processing complex 3D and live cell microscopy data, making analysis accessible.

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Fabrication of a Multiplexed Artificial Cellular MicroEnvironment Array

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Published on: September 7, 2018

Area of Science:

Microscopy and Computational Biology
Bioimage Analysis
Quantitative Imaging

Background:

Increasing complexity of microscopy necessitates advanced computational workflows for image analysis.
Current solutions often lack flexibility, interactivity, and intuitive interfaces for non-specialists.
There is a significant need for integrated software for analyzing complex 3D and live cell imaging data.

Purpose of the Study:

To present Cecelia, a toolbox designed to make quantitative multidimensional image analysis accessible.
To integrate various open-source packages into a coherent data management suite.
To provide an unbiased approach for distinguishing dynamic cell behaviors in live imaging data.

Main Methods:

Integration of multiple open-source software packages into a unified toolbox.
Development of a user-friendly interface (Shiny app) for data management and analysis.
Application of the toolbox to analyze immunologically relevant scenarios and live cell imaging data.

Main Results:

Cecelia provides a coherent data management suite for quantitative multidimensional image analysis.
The toolbox successfully integrates various open-source packages, enhancing accessibility for non-specialists.
An unbiased method was developed to distinguish dynamic cell behaviors from live imaging data.

Conclusions:

Cecelia offers a valuable framework for researchers needing accessible quantitative image analysis.
The toolbox addresses the need for integrated solutions for complex 3D and live cell imaging.
The developed approaches are expected to benefit a broad range of biological researchers.