1. IGP NCRR Image and Geometry Processing Highlights of ongoing work Geometry processing Shape analysis Visualization/segmentation

2. IGP NCRR Geometry Processing/Modeling Volumes Label Maps Correct Topology Surface Meshes Body-Fitted Meshes Segmentation Tools Segmentation Tools Volumetric Topology Filtering Antialiasing Volumetric Topology Filtering Antialiasing Meshing: Adaptive, Geometrically Regular Meshing: Adaptive, Geometrically Regular Integrate 3rd Party Packages (Tets) Integrate 3rd Party Packages (Tets)

3. IGP NCRR Shape Analysis Correspondences Geodesics on Solid Shapes

4. IGP NCRR Shape Correspondence Problem Shape metrics that rely on correspondence Correspondence depends on context of ensemble

5. IGP NCRR Particle Systems for Adaptive Surface Sampling Meyer et al., Under review, IEEE Vis 2006

6. IGP NCRR A Particle-Based Approach Minimize shape and ensemble entropy Cates et al., To appear MICCAI 2006 Workshop on Foundations of Computational Anatomy

7. IGP NCRR Statistical Shape Analysis

8. IGP NCRR Geodesics of Solid Shapes Fletcher and Whitaker, To appear MICCAI 2006 Workshop on Foundations of Computational Anatomy

9. IGP NCRR Segmentation Research Neighborhood statistics Manifolds in high-dimensional spaces Filtering, compression, segmentation, visualization Strategy Nonparametric density estimation Engineering issues

10. IGP NCRR MRI Head Segmentation MICCAI 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 85 87 89 91 93 95 97 0%1%3%5%7%9% ProposedLeemput

11. IGP NCRR Cell/Texture Segmentation Nonparametric density estimation – image neighorhoods Texture Partition image to reduce in-class entropy Random initialization Fast (nonlocal) level-set method Collab: NCMIR, Marc

12. IGP NCRR IGP Research Plans Continued development of meshing capabilities Shape analysis development and application Applications of neighborhood statistics to visualization of complex data