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. Trefethen Co-I. Dr. Vicente Grau Project 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