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Cloud Computing Framework Design for Cancer Imaging Research

Cloud Computing Framework Design for Cancer Imaging Research. 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

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Cloud Computing Framework Design for Cancer Imaging Research

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  1. Cloud Computing Framework Design for Cancer Imaging Research 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, UK 2. Dept. of Eng. Science, University of Oxford, UK 3. Radiology, Nuffield Dept. of Medicine, Churchill Hospital, University of Oxford, UK

  2. 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

  3. 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

  4. 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: Noisy, Highly textured, Poor contrast relative to their surroundings. Coronal MR image of the colorectum

  5. 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)

  6. Lowering the Barriers to Cancer Imaging • 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

  7. Lowering the Barriers to Cancer Imaging • APPLICATION DESIGN • Use of Collaborative visual tools (including multi-touch and interactive surfaces) to improve visual data input and enhance user interaction.

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

  9. Scientific Workflow Workbench Web-based Application & Virtual Research Environment Cancer Imaging Cloud Computing Framework Code Matlab, C++, Java Experimental data Additional data Enriched Desktop Application Presentations Data Reports Logs Images Publication list Image processing & Visualization toolkits User interface tools Workflows Metadata Web Services My Experiment Carmen Research Information Centre, RIC SciRun IRIS Explorer Matlab Taverna Microsoft Workflow Foundation WS WS WS

  10. 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)

  11. 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/

  12. 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

  13. Future work

  14. 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.

  15. 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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