Bisque (Bio-Image Semantic Query User Environment) is a web-based system that provides secure image storage, sharing, management and analysis. Bisque exposes every element as web-accessible resources (files, images, annotations, analysis, etc.) utilizing standard web protocols HTTP/HTTPS and XML, allowing seamless scalability and performance that build on well-developed and supported technologies. Everything in Bisque is built for flexibility: annotations, access to pixel data and custom analysis. The powerful html5-based user interface delivers only the required data to the client thus allowing simple access to massive amounts of data.
The Bisque system is integrated with iPlant's authentication system, Data Store, and computation infrastructure for scalability and ready access to a large set of downstream analysis options. For developers wanting to integrate existing applications or create new ones, Bisque provides a rich set of custom visualizations, image handling routines and APIs (Application Programming Interfaces) for building scalable, web-based image analysis applications.
- Enables storage and flexible annotations of image and arbitrary file data.
- Original file data is never altered.
- Annotations support any schema and are fully customizable.
- Easy to use 5D graphical annotations with semantic meaning and measurements.
- Image view combines manual and automated (analysis) annotations in one concise view.
- All annotations and analysis carry full provenance.
- Share results, images, and annotations with collaborators securely.
- Support for cloud and enterprise storage: iRODS, Amazon S3, local RAID.
- Great support for 200+ bio-medical image and movie formats.
- Seamless support for very large 5D images (100+ GB) with many channels and most voxel formats.
- Distributed and parallelized processing.
- No plug-ins HTML5 user interface.
- Displays 100K x 100K pixel images on a standard web browser.
- Allows measurements: count, length, area.
- Allows result comparison of different analysis.
- Enables high-throughput image analysis (Condor).
- Automatic data-parallelized processing.
- Customizable automatic web user interface for any analysis (executables, Matlab, python, etc.).
- Developers can easily publish novel analysis methods and make them web accessible.
- Developers can produce interactive plots and visualizations using the built-in API.
- Is free and open-source.
The Bisque system includes analysis algorithms useful to plant scientists as well as the broader biological research community:
- Seed size (Edgar Spalding group, University of Wisconsin).
- Root tip tracking (Edgar Spalding group, University of Wisconsin).
- Pollen tube tracking (Ravi Palanivelu group, University of Arizona).
- Nuclear detector and tracker.
- Other general biological image analysis algorithms.
|B.S. Manjunath||Bisque project lead||University of California, Santa Barbara|
|Kris Kvilekval||Lead Developer||University of California, Santa Barbara|
|Dmitry Fedorov||Lead Developer||University of California, Santa Barbara|
|Christian Wheat||Developer||University of California, Santa Barbara|
|Utkarsh Gaur||Developer||University of California, Santa Barbara|