a virtual research environment for cancer imaging (vre-ci)

3
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. 18 months 01/05/2009 – 31/10/2010. Project Partner: Microsoft Research Lee Dirks Alex Wade Roger Barga Team members: PI. Prof. Anne E. Trefethen Co-I. Dr. Vicente Grau Project Manager Dr. M. Susana Avila- Garcia. Technical developer: Dr. Pin Hu. http://www.oerc.ox.ac.uk/research/vre-ci

Upload: tarmon

Post on 23-Feb-2016

29 views

Category:

Documents


0 download

DESCRIPTION

A Virtual Research Environment for Cancer Imaging (VRE-CI). JISC VRE frameworks phase 3. 18 months 01/05/2009 – 31/10/2010. Project Partner: Microsoft Research Lee Dirks Alex Wade Roger Barga Team members: PI. Prof. Anne E. Trefethen Co-I. Dr. Vicente Grau - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: A Virtual Research Environment for Cancer Imaging (VRE-CI)

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 3.18 months 01/05/2009 – 31/10/2010. 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 developer: Dr. Pin Hu.

http://www.oerc.ox.ac.uk/research/vre-ci

Page 2: A Virtual Research Environment for Cancer Imaging (VRE-CI)

VRE-CI

Extend the functionality of the Research Information Centre (RIC) and include tools for articulating and sharing imaging algorithms through the integration of Trident.

Page 3: A Virtual Research Environment for Cancer Imaging (VRE-CI)

Current activities

Initial experiences: Installation of the RIC. Licensing

Becoming familiar with the RIC architecture. Defining data models:

Using and adapting both DICOM information model and the data model defined by the Cancer Biomedical Informatics Grid (caBIG) of the National Cancer Institute. https://cabig.nci.nih.gov/

• Ensure automatic population of image metadata when loading DICOM files. Investigating into analysis models (algorithms, inputs & results)

Developing Web parts and Web services for algorithms for cancer image segmentation.

Working with the technical administrator and developer of the Gray Institute to address the access to their server and data.