KAUST Grant NumberKUS-C7–076-04
Permanent link to this recordhttp://hdl.handle.net/10754/597676
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AbstractAdvances in computational geometric modeling, imaging, and simulation let researchers build and test models of increasing complexity, generating unprecedented amounts of data. As recent research in biomedical applications illustrates, visualization will be critical in making this vast amount of data usable; it's also fundamental to understanding models of complex phenomena. © 2012 IEEE.
CitationJohnson C (2012) Biomedical Visual Computing: Case Studies and Challenges. Computing in Science & Engineering 14: 12–21. Available: http://dx.doi.org/10.1109/mcse.2011.92.
SponsorsI'm grateful for the significant help I received from Rob MacLeod, Tolga Tasdizen, Liz jurris, jens Krüger, Tom Fogal, Nathan Galli, and Katharine Coles, and for the data from our biomedical collaborators john Triedman, Matt Jolley, Robert Marc, Bryan Jones, Erik Jorgenson, and Chris Butson. This work was supported in part by grants from the US National Science Foundation, the US Department of Energy, a grant from King Abdullah University of Science and Technology (award no. KUS-C7–076-04), and from the US National Institutes of Health/National Center for Research Resource's Center for Integrative Biomedical Computing, grant no. 2P47 RR0112553–12.
CollectionsPublications Acknowledging KAUST Support
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