Mapping bioimage-analysis software adoption in microscopy
- 1Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal; Gulbenkian Institute for Molecular Medicine, Oeiras,
Abstract
Most quantitative microscopy measurements pass through image-analysis software, and different programs can return different measurements from the same images. Which programs researchers rely on therefore matters for reproducibility; however, this information lies scattered across the methods sections of the microscopy literature. In this analysis, we show how mentions of 30 software packages changed across 1.7 million full-text microscopy papers published between 2010 and 2025. In 2010, 12% of these papers mentioned at least one of the 22 analysis packages we tracked; by 2025, 30% did. Mentions stayed concentrated on a few general-purpose platforms, led by ImageJ/Fiji. Newer packages are mentioned more often in particular fields, such as QuPath in pathology and napari in electron microscopy. Deep-learning methods are usually mentioned alongside an established platform; papers often run StarDist inside Fiji and Cellpose on its own. Many papers mention a package without citing it, so citation counts understate how often packages appear in published work; authors should make that use visible by citing each package and reporting how they ran it.
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BibTeX
@misc{shakespeare2026mapping,
title = {{Mapping bioimage-analysis software adoption in microscopy}},
author = {T. Shakespeare and B. M. Saraiva and I. Cunha and C. Jacobs and G. Jacquemet and R. Henriques},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.21.760457},
url = {https://www.biorxiv.org/content/10.64898/2026.10.21.760457v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Mapping bioimage-analysis software adoption in microscopy
AU - T. Shakespeare
AU - B. M. Saraiva
AU - I. Cunha
AU - C. Jacobs
AU - G. Jacquemet
AU - R. Henriques
PY - 2026
DA - 2026/10/21
PB - bioRxiv
DO - 10.64898/2026.10.21.760457
UR - https://www.biorxiv.org/content/10.64898/2026.10.21.760457v1
AB - Most quantitative microscopy measurements pass through image-analysis software, and different programs can return different measurements from the same images. Which programs researchers rely on therefore matters for reproducibility; however, this information lies scattered across the methods sections of the microscopy literature. In this analysis, we show how mentions of 30 software packages changed across 1.7 million full-text microscopy papers published between 2010 and 2025. In 2010, 12% of these papers mentioned at least one of the 22 analysis packages we tracked; by 2025, 30% did. Mentions stayed concentrated on a few general-purpose platforms, led by ImageJ/Fiji. Newer packages are mentioned more often in particular fields, such as QuPath in pathology and napari in electron microscopy. Deep-learning methods are usually mentioned alongside an established platform; papers often run StarDist inside Fiji and Cellpose on its own. Many papers mention a package without citing it, so citation counts understate how often packages appear in published work; authors should make that use visible by citing each package and reporting how they ran it.
ER -