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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 11/26/2014)