1. Enabling Cloud and Grid Powered Image Phenotyping
iPlant Collaborative
I’m going to talk to you about iPlant has developed to help scale image phenotyping.

2. Motivation
High throughput imaging is essential for large-scale phenotyping.
There are many motivations for scaling image phenotyping.
I’m sure everyone here appreciates that high throughput imaging is necessary for large-scale phenotyping.
The image acquisition robots are affordable, generate a lot of data.
Many labs now have such setups in your labs, but lack a comparable platform for image analysis, and to manage images.
State of the art technologies like microscopes and multichannel images are pushing the boundaries for storage and computational capabilities

3. Motivation II New, improved analysis algorithms are being published.
Metadata is key for managing large datasets.
Sharing and collaborating with large image data sets is challenging.
Difficult for biologists to use because may be command line implementations, may not handle their file format, etc.
Difficult to compare efficacy of different algorithms if in different applications, platforms.
Ship hard drives around.
Maybe your favorite analysis method is in MatLab, maybe in ImageJ.
One size doesn’t fit all:
iPlant has more than one way to help with image phenotyping:
Analysis algorithms that do NOT have GUI, and are coded in Matlab, Python, Java or C++ can be directly integrated into Bisque.
Image analysis applications with GUIs or complex software dependencies, can be installed in Atmosphere for access to large-scale storage and computing.
Biologists struggle to use them.
Developers need images to test algorithms.
Scientists need to compare algorithms, reproduce results

4. Bisque Image Management, Analysis, Sharing System

5. Why Bisque?
Integrated with iPlant storage and computation infrastructure for scalability
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

6. iPlant Computational Infrastructure
How does it work?
iPlant Computational Infrastructure
Bisque
High Bandwidth
Transfer
High Bandwidth
Transfer
This is a schematic of how Bisque fits into the iPlant ecosystem.
iPlant Data Store

7. 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)
Includes features you’re accustomed to using in photo sharing sites and Google maps.
It scales so you can analyze large datasets.

8. 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

9. MultiRoot Growth Analysis
Time lapse image stack of seeds growing
Root tip tracking by Bisque
Source: Edgar Spalding

10. Seed Size Analysis High resolution flat bed scanner image of seeds
Edge detection and analysis by Bisque
Source: Edgar Spalding

11. Automated Pollen Identification
Coming Attraction!
Imagine some pollen grains
Imagine the species of the pollen grains has been identified
Source: Matina Donaldson-Matasci, et al.

12. Projects Using Bisque 3 Graduate courses 2 Summer courses/workshops
NSF ADBC Thematic Collections Network (Yale University led)
AISO’s interactive segmentation algorithm and use of Plant Ontologies are being integrated into Bisque
Segmentation of Maize leaf lesions
Yale project is Digitizing Herbarium Collections and storing the images in Bisque
AISO (Annotation of Image Segments with Ontologies) is a project led by Pankaj Jaiswal at Oregon State University
Maize leaf lesions project is led by Toni Kazic at U Missouri

13. 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)

14. Useful Links Main application: Support: Project Website
bisque.iplantc.org
Support:
Project Website