IGP NCRR Image and Geometry Processing Highlights of ongoing work •Geometry processing •Shape analysis •Visualization/segmentation
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IGP
NCRR
Image and Geometry Processing
Highlights of ongoing work•Geometry processing•Shape analysis•Visualization/segmentation
IGP
NCRR
Geometry Processing/Modeling
Volumes Label Maps
Corre
ct T
opol
ogy
Surface Meshes
Body-Fitted Meshes
SegmentationTools
VolumetricTopology Filtering
Antialiasing
Meshing: Adaptive, Geometrically Regular
Integrate 3rd Party Packages (Tets)
IGP
NCRR
Shape AnalysisCorrespondencesGeodesics on Solid Shapes
IGP
NCRR
Shape Correspondence ProblemShape metrics that rely on
correspondence
Correspondence depends on context of ensemble
IGP
NCRR
Particle Systems for Adaptive Surface Sampling
Meyer et al., Under review, IEEE Vis 2006
IGP
NCRR
A Particle-Based ApproachMinimize shape and ensemble entropy
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QuickTime™ and aTIFF (Uncompressed) decompressor
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QuickTime™ and aTIFF (Uncompressed) decompressor
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QuickTime™ and aTIFF (Uncompressed) decompressor
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Cates et al., To appear MICCAI 2006 Workshop on Foundations of Computational Anatomy
IGP
NCRR
Statistical Shape Analysis
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IGP
NCRR
Geodesics of Solid Shapes
Fletcher and Whitaker, To appear MICCAI 2006 Workshop on Foundations of Computational Anatomy
IGP
NCRR
Segmentation Research
Neighborhood statistics•Manifolds in high-dimensional
spaces• Filtering, compression,
segmentation, visualizationStrategy•Nonparametric density
estimation• Engineering issues
IGP
NCRR
MRI Head SegmentationMICCAI 2005, MedIA to appear
MRI Input GM, WM, CSF Seg. Comparison: SOTA–EM w/MRFs & Atlas(Leemput et al.)
GM Classification Performance vs Noise Level
Collab: Makeig-Worrell, Wolters, Warfield, McIntyre
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0% 1% 3% 5% 7% 9%
Proposed Leemput
IGP
NCRR
Cell/Texture SegmentationNonparametric density estimation – image neighorhoods
• TexturePartition image to reduce in-class entropyRandom initializationFast (nonlocal) level-set method
Collab: NCMIR, Marc
IGP
NCRR
IGP Research PlansContinued development of
meshing capabilitiesShape analysis development
and applicationApplications of neighborhood
statistics to visualization of complex data
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