BIOMERO: A scalable and extensible image analysis framework

被引:0
|
作者
Luik, Torec T. [1 ]
Rosas-Bertolini, Rodrigo [1 ]
Reits, Eric A. J. [1 ]
Hoebe, Ron A. [1 ]
Krawczyk, Przemek M. [1 ]
机构
[1] Amsterdam UMC, Dept Med Biol, NL-1105 AZ Amsterdam, North Holland, Netherlands
来源
PATTERNS | 2024年 / 5卷 / 08期
基金
荷兰研究理事会;
关键词
D O I
10.1016/j.patter.2024.101024
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the rapidly evolving field of bioimaging, the integration and orchestration of findable, accessible, interoperable, and reusable (FAIR) image analysis workflows remains a challenge. We introduce BIOMERO (bioimage analysis in OMERO), a bridge connecting OMERO, a renowned bioimaging data management platform; FAIR workflows; and high-performance computing (HPC) environments. BIOMERO facilitates seamless execution of FAIR workflows, particularly for large datasets from high-content or high-throughput screening. BIOMERO empowers researchers by eliminating the need for specialized knowledge, enabling scalable image processing directly from OMERO. BIOMERO notably supports the sharing and utilization of FAIR workflows between OMERO, Cytomine/BIAFLOWS, and other bioimaging communities. BIOMERO will promote the widespread adoption of FAIR workflows, emphasizing reusability, across the realm of bioimaging research. Its user-friendly interface will empower users, including those without technical expertise, to seamlessly apply these workflows to their datasets, democratizing the utilization of AI by the broader research community.
引用
收藏
页数:9
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