Handle URI:
http://hdl.handle.net/10754/597676
Title:
Biomedical Visual Computing: Case Studies and Challenges
Authors:
Johnson, Christopher
Abstract:
Advances 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.
Citation:
Johnson 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.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
Computing in Science & Engineering
KAUST Grant Number:
KUS-C7–076-04
Issue Date:
Jan-2012
DOI:
10.1109/mcse.2011.92
PubMed ID:
22545005
Type:
Article
ISSN:
1521-9615
Sponsors:
I'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.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorJohnson, Christopheren
dc.date.accessioned2016-02-25T12:44:13Zen
dc.date.available2016-02-25T12:44:13Zen
dc.date.issued2012-01en
dc.identifier.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.en
dc.identifier.issn1521-9615en
dc.identifier.pmid22545005en
dc.identifier.doi10.1109/mcse.2011.92en
dc.identifier.urihttp://hdl.handle.net/10754/597676en
dc.description.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.en
dc.description.sponsorshipI'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.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectBiomedical computingen
dc.subjectimage analysisen
dc.subjectsimulationen
dc.subjectvisualizationen
dc.titleBiomedical Visual Computing: Case Studies and Challengesen
dc.typeArticleen
dc.identifier.journalComputing in Science & Engineeringen
dc.contributor.institutionUniversity of Utah, Salt Lake City, United Statesen
kaust.grant.numberKUS-C7–076-04en

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