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BISQUE:Enabling Cloud and Grid Powered

Image Analysis

Ramona WallsiPlant Collaborative

rwalls@iplantcollaborative.arizona.eduAdapted from slides by Martha Narro, Nirav Merchant

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Motivation I

• High throughput imaging is essential for large-scale phenotyping.• Affordable robotics for image

acquisition are creating vast amounts of imaging data.

• Many laboratories have automated imaging setups, but lack a comparable analysis platform.

• Super resolution microscopy and multi-channel images are pushing the boundaries of storage and computational capabilities.

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Motivation II• New, improved analysis

algorithms are being published.• Biologists struggle to use

them.• Developers need images to

test algorithms.• Scientists need to compare

algorithms, reproduce results.

• Metadata is key for managing large datasets.• Sharing and collaborating with large image data

sets is challenging.

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BisqueImage Management, Analysis, Sharing System

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Why Bisque?• Biologists can

• Manage images• Choose from multiple analysis options • Overlay results to validate findings• Annotate images• Share images, results, annotations via secure link • Algorithm developers can

• Publish new analysis methods, easily make them web accessible

• Produce interactive plots, visualizations using built in API• Integrated with iPlant storage and computation

infrastructure for scalability

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How does it work?

Bisque

iPlant Data Store

High B

andw

idth

Trans

fer

iPlant Computational Infrastructure

High Bandwidth

Transfer

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Bisque Features

• Web application• Tiling, zooming, step through image stacks, play as

movie• Display 20K x 20K pixel images in web browser• Handles 100+ image, video formats• Import large image sets (≤ 40 GB via Bisque),

extremely large ones (> 40 GB via iPlant Data Store)• Scale analyses using distributed computing

(connected to XSEDE) and workflow engines (Pegasus, Condor)

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Import and Export

•support for multiple files•plugin free HTML5 uploads•drag/drop• import annotations•processing compressed files•compose 5D from multiple files

•on the file streaming export•dataset export•export annotations•compressed files: Tar, GZip, Zip, BZip

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Sharing

• Easy modes: • “Private” and

• “Published”

• Google style sharing for resources• Using E-mails of

collaborators

• Read-only or Full access

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Example Analysis: Seed Size

High resolution flat bed scanner image of seeds

Edge detection and analysis by Bisque

Source: Edgar Spalding

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ImageJ modules

• Bisque API for ImageJ• Dataset Cluster/parallel execution• Run image macros/plugins using

Web-interface• Currently requires hand editing of

macro files.• Working on semi-automated

conversion

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Bisque-iPlant Team

• Bisque (U. California, Santa Barbara)• B. S. Manjunath• Kris Kvelikval• Dmitry Fedorov

• iPlant (U. Arizona, Tucson)• Nirav Merchant• Martha Narro

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• Main application:• bisque.iplanctc.org

• BISQUE video tutorials:• http://bovary.iplantcollaborative.org/client_service/

help

• Support• http://ask.iplantcollaborative.org

Useful Links