Enabling Cloud and Grid Powered Image Phenotyping
description
Transcript of Enabling Cloud and Grid Powered Image Phenotyping
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Enabling Cloud and Grid PoweredImage Phenotyping
Martha NarroiPlant Collaborative
[email protected] from slides by Nirav Merchant
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Motivation• High throughput imaging is
essential for large-scale phenotyping.• Affordable robotics for image
acquisition 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.• ONE SIZE FITS ALL APPROACH DOES NOT WORK
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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 Ban
dwidt
h
Transfe
r
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 Bisque), extremely
large ones (> 40 GB iPlant Data Store)• Scale analyses using distributed computing
(connected to XSEDE) and workflow engines (Pegasus, Condor)
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Pollen Tube Tracker Analysis
Stack of time-lapse images of pollen tubes growing in vitro displaying maximum intensity in each image Tracking by Bisque
Source: Ravi Palanivelu, Kobus Barnard
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MultiRoot Growth Analysis
Time lapse image stack of seeds growing Root tip tracking by Bisque
Source: Edgar Spalding
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Seed Size AnalysisHigh resolution flat bed scanner image of seeds
Edge detection and analysis by Bisque
Source: Edgar Spalding
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Automated Pollen Identification
Imagine some pollen grains
Source: Matina Donaldson-Matasci, et al.
Imagine the species of the pollen grains has been identified
Coming Attraction!
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Users
Currently iPlant has 5+ groups actively using this infrastructure•3 Graduate courses•2 Summer courses/workshops•NSF ADBC Thematic Collections Network(Yale University led)
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Users
Currently iPlant has 5+ groups actively using this infrastructure•3 Graduate courses•2 Summer courses/workshops•NSF ADBC Thematic Collections Network(Yale University led) •Welcome, 1 Pollen RCN
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Bisque-iPlant Team
• Bisque (U. California, Santa Barbara)• B. S. Manjunath• Kris Kvelikval• Dmitry Fedorov• Phytomorph (U. Wisconsin, Madison)
• Edgar Spalding• Nathan Miller• Logan Johnson• Nirav Merchant (iPlant; U. Arizona, Tucson)
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• Main application:• bisque.iplantc.org• Support:
• http://ask.iplantcollaborative.org• Project Website
• http://www.iplantcollaborative.org
Useful Links