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Bisque: A platform for bioimage analysis and management

Lookup NU author(s): Professor Boguslaw ObaraORCiD

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Abstract

Motivation: Advances in the field of microscopy have brought about the need for better image management and analysis solutions. Novel imaging techniques have created vast stores of images and metadata that are difficult to organize, search, process and analyze. These tasks are further complicated by conflicting and proprietary image and metadata formats, that impede analyzing and sharing of images and any associated data. These obstacles have resulted in research resources being locked away in digital media and file cabinets. Current image management systems do not address the pressing needs of researchers who must quantify image data on a regular basis. Results: We present Bisque, a web-based platform specifically designed to provide researchers with organizational and quantitative analysis tools for 5D image data. Users can extend Bisque with both data model and analysis extensions in order to adapt the system to local needs. Bisque's extensibility stems from two core concepts: flexible metadata facility and an open web-based architecture. Together these empower researchers to create, develop and share novel bioimage analyses. Several case studies using Bisque with specific applications are presented as an indication of how users can expect to extend Bisque for their own purposes. Availability: Bisque is web based, cross-platform and open source. The system is also available as software-as-a-service through the Center of Bioimage Informatics at UCSB. Contact: kris@cs.ucsb.edu; fedorov@ece.ucsb.edu Supplementary information: The supplementary material is available at Bioinformatics online, including screen shots, metadata XML descriptions and implementation details. © The Author 2009. Published by Oxford University Press.


Publication metadata

Author(s): Kvilekval K, Fedorov D, Obara B, Singh A, Manjunath BS

Publication type: Article

Publication status: Published

Journal: Bioinformatics

Year: 2009

Volume: 26

Issue: 4

Pages: 544-552

Print publication date: 15/02/2010

Online publication date: 22/12/2009

ISSN (print): 1367-4803

ISSN (electronic): 1460-2059

Publisher: Oxford University Press

URL: https://doi.org/10.1093/bioinformatics/btp699

DOI: 10.1093/bioinformatics/btp699

PubMed id: 20031971


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