Bridging annotated microscopy imaging data and analysis method development for scientific discovery.
Where this comes from
- Record sourced from PubMed, PMID 42328198.
- Also identified by DOI 10.1016/j.patter.2026.101542 and PMC identifier 13280720.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
While modern imaging technologies offer unprecedented opportunities to observe life across scales, distilling an understanding of the underlying biological processes from these complex, high-dimensional data remains challenging. Computational analysis methods have been lagging behind our ability to produce data, as their development often requires expertise across multiple domains, including life and computer sciences. Annotated image datasets play a key role in fostering the development and improvement of microscopy image analysis methods, as they offer a realistic basis to build upon and invaluable ground truth to evaluate and optimize performance. Drawing inspiration from adjacent fields to microscopy imaging, we discuss in this perspective how sharing annotated datasets has driven progress in computational analysis. We emphasize the critical role that open data standards and infrastructure play in realizing the full scientific potential of annotated image datasets and close by highlighting opportunities for members across the scientific community to cultivate a dynamic ecosystem of data, infrastructure, and analysis methods to elevate research quality and accelerate innovation.