CellScore: an open-source image-based pipeline for automated cell quantification in microalgae

Abstract Accurate quantification of microalgal cell density is essential for both basic research and industrial applications, as it directly reflects culture growth, productivity, and physiological status. There are existing methods routinely used to measure cell counts, although many are limited by high cost, labor-intensive workflows, or steep technical barriers. To address these limitations, we developed CellScore, a rapid and accessible image-based pipeline for microalgal cell counting implemented in ImageJ, a widely adopted open-source platform in the biological sciences ( https://github.com/shijieh/imageJ-annotate ). By leveraging the broad user base and ease of installation of the software, CellScore enables researchers to obtain reliable cell counts from standard microscopy images with minimal specialized equipment. Although the workflow has only been tested with three microalgae species of similar morphologies, the pipeline balances automation with user control and includes practical troubleshooting strategies to facilitate adoption by new users. Thus, CellScore has the potential to be used broadly across other species, however, broader validation across diverse morphologies is required. Overall, CellScore provides a cost-effective, user-friendly, and reproducible solution for routine microalgal cell quantification in both laboratory and applied settings.