Mapping bioimage-analysis software adoption in microscopy

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. We tracked 32 software entries across 1.7 million full-text microscopy papers published between 2010 and 2025. In 2010, 15% of these papers mentioned at least one of the 23 analysis packages in our aggregate; by 2025, 31% did. Mentions stayed concentrated on a few general-purpose platforms, led by ImageJ/Fiji. Papers mentioning newer packages more often use the vocabulary of particular fields, such as pathology terms with QuPath and electron-microscopy terms with napari. Deep-learning methods are usually mentioned alongside an established platform; in sampled papers, StarDist often ran 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.