Rapid and reliable image analysis pipeline for semi-automated quantification of CNS cell types in MATLAB

This study presents an alternative to classical segmentation models by offering a reproducible quantification of CNS-resident cells using nuclear morphology. Its simplicity, minimal input requirements, reduced time for semi-automated quantification, and specificity for CNS tissues make it a valuable tool for studying cellular responses in both healthy and pathological contexts.

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Publication Details

Journal
Journal of Neuroscience Methods
Published
2025-09-25
DOI
https://doi.org/10.1016/j.jneumeth.2025.110590
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
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article

Rapid and reliable image analysis pipeline for semi-automated quantification of CNS cell types in MATLAB

Steve Lacroix, Adrian Castellanos-Molina, Ana Boisvert, Nicolas Vallières et al.
Journal of Neuroscience Methods
Cell Image Analysis Techniques
article

Rapid and reliable image analysis pipeline for semi-automated quantification of CNS cell types in MATLAB

Steve Lacroix, Adrian Castellanos-Molina, Ana Boisvert, Nicolas Vallières, J. Ferry, Alexandre Chamberland
article en

Abstract

This study presents an alternative to classical segmentation models by offering a reproducible quantification of CNS-resident cells using nuclear morphology. Its simplicity, minimal input requirements, reduced time for semi-automated quantification, and specificity for CNS tissues make it a valuable tool for studying cellular responses in both healthy and pathological contexts.

Journal of Neuroscience MethodsVol. 424
Centre hospitalier universitaire de Québec (CA), Centre hospitalier de l'Université Laval (CA), Université Laval (CA)
Openalex Percentile: Top 81%
Cell Image Analysis Techniques
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