BisQue is developed at the Center for Bio-Image Informatics at University of California, Santa Barbara. The BisQue system supports several areas useful for imaging researchers from image capture to image analysis and querying.
Centered around a database of images and metadata, BisQue supports search and comparison of image datasets. Novel semantic analyses are integrated into the system, allowing high-level semantic queries and comparison of image content.
BisQue is integrated with CyVerse's authentication system, the Data Store, and computation infrastructure for scalability and ready access to a large set of downstream analysis options.
Developers can integrate existing applications or create new ones, leveraging BisQue's rich set of custom visualizations, image handling routines, and APIs (Application Programming Interfaces) for building scalable, web-based image analysis applications. Before you can use BisQue, you must have a CyVerse account and be granted access to BisQue.
- Free and open source
- Flexible textual and graphical annotations
- Cloud scalability: Terabytes of images, millions of annotations
- Distributed storage: local, iRODS, S3
- Integrated image analysis, high-throughput with Condor
- Analysis in MATLAB, Python, Java+ImageJ
- 100+ biological image formats; Formats from other domains can be supported
- Very large 5D images (100+ GB)