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Presented by Maria Susanna Avila Garcia at the JISC Future of Research Conference, 19th October 2010
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RIC Workshop
26 July 2010
A Virtual Research Environment for Cancer Imaging (VRE-CI)
Outline
Background Project Overview DICOM Image functionality Image analysis Sharing project outputs Questions
Background
Implementing algorithms developed in the past by other researchers.
Reusing existing pieces of code. Sharing is an issue since they commonly use
different programming tools, data sources and formats.
Feedback Show result on a computer/laptop screen. Do not have the opportunity to interact with the
applications. No user interface defined for them
They work at different locations Computing Lab
Hospital
Sharing image datasets.
Virtual Research Environment
Research Context
Web Services
Code
Scientific Workflows/Activities
End users
Sharing algorithm to:•Reuse it as it is.•Reuse it as part of a bigger solution.•Modify it.
Test the algorithm:• Original data• Own data
• Different image formats
A Virtual Research Environment for Cancer Imaging (VRE-CI)
VRE-CI project is funded by the Joint Information Systems Committee (JISC) to provide a framework to allow researchers and clinicians involved in Cancer Imaging to share information, images and algorithms. JISC VRE frameworks phase 3. 22 months 01/05/2009 – 28/02/2011. Project Partner: Microsoft Research
Lee DirksAlex WadeRoger Barga
Team members:PI. Prof. Anne E. TrefethenCo-I. Dr. Vicente GrauProject Manager Dr. M. Susana Avila-Garcia.Technical developers: Xin Xiong, Charles Crichton and Andrew Tsui.
VRE-CI
Use cases
Oncological image analysis• Leveraging the work of an existing Microsoft funded project
on the development of novel segmentation algorithms for colorectal cancer images.
• Use case to ensure that the main elements of cancer imaging research are considered.
Fluorescent microscopy. • Gray Institute of Radiation, Oncology and Biology.
• Ensure the system is interoperable with existing image management systems.
Project Outputs
Module for Cancer Imaging: Sharing DICOM images
• Load in the system• Creating links to other servers
Sharing Image processing algorithms:• Workflows/activities• Web services
Advanced search. • Image DICOM & Keyword metadata• Algorithms
Architecture being defined to add more image formats, algorithms.
Loading images into the system
More secure way to make images available to researchers. Ensuring datasets are ‘validated’. Avoid storing data in media that might not be
stored/managed securely. Clinicians may have a way to track which datasets
they have made available and the associated results back from researchers.
Subjects
Confidential information
Anonymised data sets
No confidential information
No need to remove any metadata
Define personalised filters to fit needs from each user/research scenario
Configuration Files
Use of configuration files to personalise metadata filters according to each user preferences.
Loading images
Image Metadata
Dicom Image Properties / Zoom in
Image Viewer
Adapt an existing Deep Zoom viewer [http://images.cancergrid.org/score/]
Need a DICOM image filter to convert to bmp or jpeg format. Developed using the Insight Toolkit ITK.
What is Silverlight DeepZoom?
Multiple layers at different resolutions
Enables quick zooming and panning of large images
Requires Silverlight browser plugin
Image Viewer / Deep zoom functionality
Image analysis
Scientific Workflows/ Trident
This graphical representation hides the complexity of the applications allowing to: • understand at a high level how the application works, • modify the flow of activities in an easy way and • analyse the application into the level of required detail
– http://www.microsoft.com/mscorp/tc/trident.mspx
Oxford University Groupware
Oxford University has adopted a Microsoft solution as the integrated framework to support future communications and collaboration across the University.
This project will provide an exemplar within the realm of the Virtual Research Environment and will result, we hope in a model that can be utilised in other parts of the University.
SharePoint 2010 Pros & Cons
Pros:
•When University has the license•Can be supported on the cloud
• SP admin not required• Could lead to more
effective (cheaper) use of computer systems.
• Could lead to less computer support required.
Cons:
•If not this is expensive•Uncertain business model at this time
Acknowledgements
Dr Niranjan Joshi Interviewees at Gray Institute of Radiation Oncology and Biology.
Sean Smart, Danny Allen Veerle Kersemans & Bart Cornelissen.
Advisory committee. Peter Jezzard, Paul Watson.
British Library – Stephen Andrews
Thanks!
Questions?
Project website: http://www.oerc.ox.ac.uk/research/vre-ci