Cloud Computing Framework Design for Cancer Imaging Research

Cloud Computing Framework Design for Cancer Imaging Research

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 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 Corporation: Initiative project funded by

Microsoft 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. PIs Prof Anne E. Trefethen and Prof Sir Mike Brady (OERC) 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 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. Cloud Computing Framework Provenance Security Various levels of information access to provide security and data confidentiality when needed contributions of each user are registered. Web Services Cancer Imaging Cloud Computing Framework Metadata

Experiment Metadata Manage the concept of experiments where links Efficient access to the most upto various objects can lead the researcher to to-date, authoritative knowledge the information required. that can serve as metadata Provenance Collaboration environment contributions of each researcher are Provide discussion forums to enable registered and the use of their

communication and collaboration among methods and experimental data is researchers acknowledged Cancer Imaging Cloud Computing Framework Code Matlab, C++, Java Experimental data Data Logs Images Image processing & Visualization toolkits Workflows

Additional data Reports Presentations Publication list User interface tools Metadata Web Services WS WS WS 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 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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