Dr. Maria Susana Avila Garcia1, Prof Anne E. Trefethen1, Prof Sir Michael Brady2, Dr Fergus
Gleeson3 and Dr. Daniel Goodman1
1. Oxford e-Research Centre, University of Oxford, UK2. Dept. of Eng. Science, University of Oxford, UK3. Radiology, Nuffield Dept. of Medicine, Churchill Hospital, University of Oxford, UK
Cloud Computing Framework Design for Cancer Imaging
Research
Outline• Colorectal Cancer• Oxford approach• Cancer and Cardiac Imaging Project• Lowering the Barrier to Cancer Imaging• Cloud Computing Framework• Microsoft Tools• Challenges• Future Work• Conclusions
Colorectal and liver cancer in UK
• According with Cancer Research UK (cited August 2008): – Approximately 36,000 people are diagnosed with colorectal cancer every
year in UK – The third most common cancer
• Colorectal cancer often metastasizes to the liver with poor prognosis, – liver cancer causes around 3,000 deaths each year.
• Medical imaging techniques such as magnetic resonance imaging (MRI), ultrasound (US), computerized tomography (CT) and a combination of positron emission tomography (PET) with CT (PET/CT), have been used for detecting, staging, and monitoring the evolution of patients
At Oxford• Researchers working in image analysis of colorectal and liver
cancer images:– Segmentation
– Registration
– Image quality improvement.
Analysis of medical images is difficult since they are:a)Noisy,b)Highly textured,c)Poor contrast relative to their surroundings.
Coronal MR image of the colorectum
Cancer and Cardiac Imaging
Technical Computing Initiative project funded by Microsoft Corporation:
Investigating the development of new segmentation algorithms for colorectal cancer imaging. Dr. Niranjan Joshi and Prof Sir Mike Brady (OERC) (Engineering Department Oxford University) and Dr. Fergus Gleeson (Churchill Hospital and Oxford University) , and Prof. Andrew Blake (Microsoft Research Cambridge)
“Lowering the Barriers to Cancer Imaging” project is aimed to maximise the efficiency of a Medical Image Analysis (MIA) researcher and to alleviate the frustration of clinicians for not being able to analyse and process images using the algorithms developed by MIA researchers. PI’s Prof Anne E. Trefethen and Prof Sir Mike Brady (OERC)
Lowering the Barriers to Cancer Imaging
SHARING RESOURCESA platform independent framework. Federated storage (data, algorithms, related
info). A repository of algorithms with no bounds to
specific programming languages. Access to already existing imaging and
visualization toolkits with no bounds to specific programming languages.
Access to the most up-to-date authoritative knowledge.
A framework for rapid development and deployment of applications for use by researchers and clinicians.
Improve mechanisms for manual segmentation
Lowering the Barriers to Cancer Imaging
APPLICATION DESIGNUse of Collaborative visual
tools (including multi-touch and interactive surfaces) to improve visual data input and enhance user interaction.
Cloud Computing Framework
SecurityVarious levels of information access to provide security
and data confidentiality when needed
Provenancecontributions of each user are
registered. Web Services
Metadata
Cancer Imaging Cloud Computing Framework
ExperimentManage the concept of experiments where links
to various objects can lead the researcher to the information required.
Collaboration environmentProvide discussion forums to enable
communication and collaboration among researchers
MetadataEfficient access to the most up-to-date, authoritative knowledge
that can serve as metadata
Provenancecontributions of each researcher are
registered and the use of their methods and experimental data is
acknowledged
Metadata
Web Services
Workflows
CodeMatlab,
C++, Java
Experimental data
Data LogsImages
Additional data
Reports
Publication list
Presentations
Image processing & Visualization toolkits User interface tools
WS
WSWS
Cancer Imaging Cloud Computing Framework
My ExperimentCarmen
Research Information Centre, RIC
TavernaMicrosoft Workflow
Foundation
SciRunIRIS Explorer
Matlab
Microsoft Tools
• Visual Studio is being already used by MIA researchers and makes it easy to add Web Service calls.
• Use .NET platform to develop application to enable the use of a unique platform– Including Microsoft Workflow Foundation.
• Collaborate with existing Virtual Research Environments:– Research Information Centre (RIC)
Challenges
•The adaptation of existing software:– Virtual research environments.– Imaging and Visualisation toolkits.– Algorithms developed by researchers.
•Link to permanent and secure online archives,
– Repository for research materials produced by scholars at Oxford University, to ensure access to a permanent and secure online archive, http://ora.ouls.ox.ac.uk/– Repositories with Cancer Images, i.e. National Cancer Imaging Archive (NCIA). https://imaging.nci.nih.gov/ncia/
Challenges
•Engage potential users:– Medical image analysis (MIA) researchers
• define the way contribution will be made.
– Engineering and computer science academics, and to undergraduate students,
• to raise interest in challenges to solve computational and software engineering problems.
•Engage medical and biomedical science academics and students with the use of image processing techniques
Future work
Conclusions
• We have presented a Cloud computing framework design to provide:– Rapid application testing and development environment for
Medical Image Analysis (MIA) researchers.– Easy access to federated resources (algorithms and data)
for both MIA researchers and Clinicians. – Support to imaging and visualization toolkits using Visual
Studio.
• We have outlined our plan for future work which includes collaboration with other projects.
Acknowledgements
This research is funded by the Technical Computing Initiative of Microsoft Corporation.
We thank MIA researchers at Oxford for their valuable comments during the analysis of requirements for this
project, especially Vicente Grau, Niranjan Joshi and Olivier Noterdaeme as well as radiologists working at Churchill and
John Radcliffe Hospitals especially Dr. Rachel R Phillips and Dr Mark Anderson.
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