Uncertainty visualization in HARDI based on ensembles of ODFs

Handle URI:
http://hdl.handle.net/10754/600126
Title:
Uncertainty visualization in HARDI based on ensembles of ODFs
Authors:
Jiao, Fangxiang; Phillips, Jeff M.; Gur, Yaniv; Johnson, Chris R.
Abstract:
In this paper, we propose a new and accurate technique for uncertainty analysis and uncertainty visualization based on fiber orientation distribution function (ODF) glyphs, associated with high angular resolution diffusion imaging (HARDI). Our visualization applies volume rendering techniques to an ensemble of 3D ODF glyphs, which we call SIP functions of diffusion shapes, to capture their variability due to underlying uncertainty. This rendering elucidates the complex heteroscedastic structural variation in these shapes. Furthermore, we quantify the extent of this variation by measuring the fraction of the volume of these shapes, which is consistent across all noise levels, the certain volume ratio. Our uncertainty analysis and visualization framework is then applied to synthetic data, as well as to HARDI human-brain data, to study the impact of various image acquisition parameters and background noise levels on the diffusion shapes. © 2012 IEEE.
Citation:
Jiao F, Phillips JM, Gur Y, Johnson CR (2012) Uncertainty visualization in HARDI based on ensembles of ODFs. 2012 IEEE Pacific Visualization Symposium. Available: http://dx.doi.org/10.1109/PacificVis.2012.6183591.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2012 IEEE Pacific Visualization Symposium
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
Feb-2012
DOI:
10.1109/PacificVis.2012.6183591
PubMed ID:
24466504
PubMed Central ID:
PMC3898522
Type:
Conference Paper
Sponsors:
Supported by NIH/NCRR Center for Integrative Biomedical Computing, 2P41-RR12553-12, Award KUS-C1-016-04, by KAUST, and DOE SciDAC VACET andDOE NETL, by subaward to the Univ. Utah under NSF award 1019343 to CRA, andby NIH Autism Center of Excellence grant (NIMH and NICHD #HD055741).
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorJiao, Fangxiangen
dc.contributor.authorPhillips, Jeff M.en
dc.contributor.authorGur, Yaniven
dc.contributor.authorJohnson, Chris R.en
dc.date.accessioned2016-02-28T06:43:13Zen
dc.date.available2016-02-28T06:43:13Zen
dc.date.issued2012-02en
dc.identifier.citationJiao F, Phillips JM, Gur Y, Johnson CR (2012) Uncertainty visualization in HARDI based on ensembles of ODFs. 2012 IEEE Pacific Visualization Symposium. Available: http://dx.doi.org/10.1109/PacificVis.2012.6183591.en
dc.identifier.pmid24466504en
dc.identifier.doi10.1109/PacificVis.2012.6183591en
dc.identifier.urihttp://hdl.handle.net/10754/600126en
dc.description.abstractIn this paper, we propose a new and accurate technique for uncertainty analysis and uncertainty visualization based on fiber orientation distribution function (ODF) glyphs, associated with high angular resolution diffusion imaging (HARDI). Our visualization applies volume rendering techniques to an ensemble of 3D ODF glyphs, which we call SIP functions of diffusion shapes, to capture their variability due to underlying uncertainty. This rendering elucidates the complex heteroscedastic structural variation in these shapes. Furthermore, we quantify the extent of this variation by measuring the fraction of the volume of these shapes, which is consistent across all noise levels, the certain volume ratio. Our uncertainty analysis and visualization framework is then applied to synthetic data, as well as to HARDI human-brain data, to study the impact of various image acquisition parameters and background noise levels on the diffusion shapes. © 2012 IEEE.en
dc.description.sponsorshipSupported by NIH/NCRR Center for Integrative Biomedical Computing, 2P41-RR12553-12, Award KUS-C1-016-04, by KAUST, and DOE SciDAC VACET andDOE NETL, by subaward to the Univ. Utah under NSF award 1019343 to CRA, andby NIH Autism Center of Excellence grant (NIMH and NICHD #HD055741).en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectDT-MRIen
dc.subjectHARDIen
dc.subjectRank-k tensor decompen
dc.subjectUncertaintyen
dc.titleUncertainty visualization in HARDI based on ensembles of ODFsen
dc.typeConference Paperen
dc.identifier.journal2012 IEEE Pacific Visualization Symposiumen
dc.identifier.pmcidPMC3898522en
dc.contributor.institutionSCI Institute, , United Statesen
dc.contributor.institutionUniversity of Utah, Salt Lake City, United Statesen
kaust.grant.numberKUS-C1-016-04en

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