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Accounting for Uncertainty in Medical Data: A CUDA Implementation of Normalized Convolution
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
2011 (English)In: Evaluations of graphics and visualization - efficiency, usefulness, accessibility, usability., 2011Conference paper, Published paper (Refereed)
Abstract [en]

The domain of medical imaging is naturally moving towards methods that can represent, and account for, localuncertainties in the image data. Even so, fast and efficient solutions that take uncertainty into account are notreadily available even for common problems such as gradient estimation. In this work we present a CUDA imple-mentation of Normalized Convolution, an uncertainty-aware image processing technique, well established in thesignal processing domain. Our results show that up to 100X speedups are possible, which enables full resolutionCT images to be processed at interactive processing speeds, fulfilling demands of both efficiency and interactivitythat exist in the medical domain.

Place, publisher, year, edition, pages
2011.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-78337OAI: oai:DiVA.org:liu-78337DiVA: diva2:532090
Conference
SIGRAD 2011, 17–18 November, Stockholm
Available from: 2012-06-09 Created: 2012-06-09 Last updated: 2012-06-29

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Lindholm, StefanKronander, Joel

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