Dr. Maria Susana Avila Garcia 1, Prof Anne E. Trefethen 1, Prof Sir Michael Brady 2, Dr Fergus Gleeson 3 and Dr. Daniel Goodman 1 1. Oxford e-Research Centre, University of Oxford, UK 2. Dept. of Eng. Science, University of Oxford, UK 3. 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 maximise the efficiency of an image analysis researcher SHARING RESOURCES  A 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 alleviate the frustration of non IT users who are not able to analyse and process images with reasonable effort APPLICATION DESIGN  Use of Collaborative visual tools (including multi-touch and interactive surfaces) to improve visual data input and enhance user interaction.

Cloud Computing Framework Security Various levels of information access to provide security and data confidentiality when needed Provenance contributions of each user are registered. Web Services Metadata Cancer Imaging Cloud Computing Framework Experiment Manage the concept of experiments where links to various objects can lead the researcher to the information required. Collaboration environment Provide discussion forums to enable communication and collaboration among researchers Metadata Efficient access to the most up- to-date, authoritative knowledge that can serve as metadata Provenance contributions of each researcher are registered and the use of their methods and experimental data is acknowledged

Web-based Application & Virtual Research Environment Metadata Web Services Workflows Code Matlab, C++, Java Experimental data Data Logs Images Additional data Reports Publication list Presentations Image processing & Visualization toolkits User interface tools Scientific Workflow Workbench Enriched Desktop Application WS Cancer Imaging Cloud Computing Framework My Experiment Carmen Research Information Centre, RIC Taverna Microsoft Workflow Foundation SciRun IRIS 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, –Repositories with Cancer Images, i.e. National Cancer Imaging Archive (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 WP0. Evaluation of existing software environment solutions to plug our use case in. Look for VRE offering similar functionality Evaluate adaptation risks Test use case functionality WP1. Design of standard datasets, metadata and web services. Collect Data and Algorithms Generate metadata information Design web services WP2. Design of workflow orchestration and enactment using Windows Workflow Foundation Look for appropriate Workflow Workbench WP3. Incorporation of existing imaging and visualization toolkits. Assess licensing issues Evaluate access mode (as.dll, WS, etc) Generate appropriate WS WP6. Links to permanent and online repositories. Look for relevant online repositories for Cancer imaging research and research publications.

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.