Cell Analyser in Batch for Neurite (CABaNe), an Automated, High-Throughput ImageJ Macro for Cell and Neurite Analysis

Measuring neurite length is crucial in neurobiology because it provides valuable insights into the growth, development, and function of neurons. In particular, neurite length is fundamental to study neuronal development and differentiation, neurons responses to drugs, neurodegenerative diseases and neuronal plasticity. Surprisingly, there is currently a lack of tools for high-throughput neurite analysis. In this article, we present CABaNe, as an open-source, high-throughput, rule-based ImageJ macro for cell analysis, including their neurite length. This macro possesses a graphical interface, metadata production, as well as verification means before and after analysis. Rule-based and machine learning-based programming have been tested for cell identification. Cell tested were N2A, a mouse neuroblastoma cell line. After testing, we had better precision and adaptability using rule-based cell identification. We challenged CABaNe with currently used techniques, which are manual or assisted. When tested on a small sample, CABaNe analyzed the dataset of interest much faster than manual measurements, while maintaining or increasing precision. When tested on a large dataset, comparing different conditions, we successfully highlighted differences between conditions, in a fully automated manner. Therefore, CABaNe is viable as a high-throughput option for cell analysis, for neurite length and other parameters. It is a base of code that can be used for other analysis or to train deep learning models. In the future, we expect this tool to be widely used in both basic and applied neurobiology research.

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Publication Details

Journal
eNeuro
Published
2026-01-30
DOI
https://doi.org/10.1523/eneuro.0193-25.2025
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Cell Analyser in Batch for Neurite (CABaNe), an Automated, High-Throughput ImageJ Macro for Cell and Neurite Analysis

Paul Machillot, Fabrice P. Cordelières, Elisa Migliorini, Catherine Picart et al.
eNeuro
Cell Image Analysis Techniques
article

Cell Analyser in Batch for Neurite (CABaNe), an Automated, High-Throughput ImageJ Macro for Cell and Neurite Analysis

Paul Machillot, Fabrice P. Cordelières, Elisa Migliorini, Catherine Picart, Akshita Singh, Nathan Thibieroz, Lisa Marchadier
article en

Abstract

Measuring neurite length is crucial in neurobiology because it provides valuable insights into the growth, development, and function of neurons. In particular, neurite length is fundamental to study neuronal development and differentiation, neurons responses to drugs, neurodegenerative diseases and neuronal plasticity. Surprisingly, there is currently a lack of tools for high-throughput neurite analysis. In this article, we present CABaNe, as an open-source, high-throughput, rule-based ImageJ macro for cell analysis, including their neurite length. This macro possesses a graphical interface, metadata production, as well as verification means before and after analysis. Rule-based and machine learning-based programming have been tested for cell identification. Cell tested were N2A, a mouse neuroblastoma cell line. After testing, we had better precision and adaptability using rule-based cell identification. We challenged CABaNe with currently used techniques, which are manual or assisted. When tested on a small sample, CABaNe analyzed the dataset of interest much faster than manual measurements, while maintaining or increasing precision. When tested on a large dataset, comparing different conditions, we successfully highlighted differences between conditions, in a fully automated manner. Therefore, CABaNe is viable as a high-throughput option for cell analysis, for neurite length and other parameters. It is a base of code that can be used for other analysis or to train deep learning models. In the future, we expect this tool to be widely used in both basic and applied neurobiology research.

eNeuroVol. 13(2)
Centre National de la Recherche Scientifique (FR), Université de Bordeaux (FR), Inserm (FR), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), CEA Grenoble (FR), Laboratoire d'Intégration des Systèmes et des Technologies (FR), Université Grenoble Alpes (FR)
Pfizer, Agence Nationale de la Recherche, Ligue Contre le Cancer
Openalex Percentile: Top 74%
Cell Image Analysis Techniques
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