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Enabling Cloud and Grid Powered Image Phenotyping. Martha Narro iPlant Collaborative [email protected] Adapted from slides by Nirav Merchant. Motivation. High throughput imaging is essential for large-scale phenotyping . - PowerPoint PPT Presentation
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www.iplantcollaborative.org
Enabling Cloud and Grid PoweredImage Phenotyping
Martha NarroiPlant Collaborative
[email protected] from slides by Nirav Merchant
www.iplantcollaborative.org
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.
www.iplantcollaborative.org
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
www.iplantcollaborative.org
BisqueImage Management, Analysis, Sharing System
www.iplantcollaborative.org
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
www.iplantcollaborative.org
How does it work?
Bisque
iPlant Data Store
High Ban
dwidt
h
Transfe
r
iPlant Computational Infrastructure
High Bandwidth
Transfer
www.iplantcollaborative.org
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)
www.iplantcollaborative.org
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
www.iplantcollaborative.org
MultiRoot Growth Analysis
Time lapse image stack of seeds growing Root tip tracking by Bisque
Source: Edgar Spalding
www.iplantcollaborative.org
Seed Size AnalysisHigh resolution flat bed scanner image of seeds
Edge detection and analysis by Bisque
Source: Edgar Spalding
www.iplantcollaborative.org
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!
www.iplantcollaborative.org
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)
www.iplantcollaborative.org
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
www.iplantcollaborative.org
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)
www.iplantcollaborative.org
• Main application:• bisque.iplantc.org• Support:
• http://ask.iplantcollaborative.org• Project Website
• http://www.iplantcollaborative.org
Useful Links
