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Authors:S. Lindholm: Department of Science and Technology, Linköping University
J. Kronander: Department of Science and Technology, Linköping University
Publication title:Accounting for Uncertainty in Medical Data: A CUDA Implementation of Normalized Convolution
Conference:Proceedings of SIGRAD 2011. Evaluations of Graphics and Visualization — Efficiency, Usefulness, Accessibility, Usability, November 17–18, 2011, KTH, Stockholm, Sweden
Publication type: Abstract and Fulltext
Issue:065
Article No.:006
Abstract:The domain of medical imaging is naturally moving towards methods that can represent, and account for, local uncertainties in the image data. Even so, fast and efficient solutions that take uncertainty into account are not readily available even for common problems such as gradient estimation. In this work we present a CUDA implementation of Normalized Convolution, an uncertainty-aware image processing technique, well established in the signal processing domain. Our results show that up to 100X speedups are possible, which enables full resolution CT images to be processed at interactive processing speeds, fulfilling demands of both efficiency and interactivity that exist in the medical domain.
Language:English
Year:2011
No. of pages:8
Pages:35-42
ISBN:978-91-7393-008-6
Series:Linköping Electronic Conference Proceedings
ISSN (print):1650-3686
ISSN (online):1650-3740
File:http://www.ep.liu.se/ecp/065/006/ecp11065006.pdf
Available:2011-11-21
Publisher:Linköping University Electronic Press, Linköpings universitet

REFERENCE TO THIS PAGE
S. Lindholm, J. Kronander (2011). Accounting for Uncertainty in Medical Data: A CUDA Implementation of Normalized Convolution, Proceedings of SIGRAD 2011. Evaluations of Graphics and Visualization — Efficiency, Usefulness, Accessibility, Usability, November 17–18, 2011, KTH, Stockholm, Sweden http://www.ep.liu.se/ecp_article/index.en.aspx?issue=065;article=006 (accessed 8/29/2014)