Mapping bioimage-analysis software adoption in microscopy
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…
Quantitative microscopy measurements rely on image-analysis software, but different programs can yield varying results. Keeping track of which software researchers depend on is crucial for achieving reproducibility, yet this information is dispersed throughout microscopy literature. Our analysis examines how references to 30 software packages evolved across 1.7 million full-text microscopy papers from 2010 to 2025.
In 2010, 12% of these papers referenced at least one of the 22 analysis packages we tracked; by 2025, this number had risen to 30%. Most of the mentions remained focused on a few general-purpose platforms, primarily ImageJ/Fiji. However, newer packages are gaining prominence in specific fields; for instance, QuPath is frequently mentioned in pathology, while napari is prominent in electron microscopy.
Deep-learning methods are typically discussed alongside established platforms, with papers often running StarDist within Fiji and Cellpose independently. Notably, many papers cite a package without providing details on how they utilized it; therefore, authors should make this information visible by citing each package and documenting their methods of usage.
Written by urgent.news from bioRxiv's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
