1. NA-MIC National Alliance for Medical Image Computing http://na-mic.org Shape Analysis and Cortical Correspondence Martin Styner Core 1 (Algorithms), UNC Ipek Oguz, Xavier Barbero, Nicolas Augier

2. National Alliance for Medical Image Computing http://na-mic.org UNC Core changes UNC core split in half –DTI research move with Guido to Utah –Shape and Structural research at UNC UNC NA-MIC Papers 2007 Shape: 1.Cates J, Fletcher PT, Styner MA, Shenton M, Whitaker R, Shape Modeling and Analysis with Entropy- Based Particle Systems, Information Processing in Medical Imaging 2007, 20:333-45. 2.Styner M, Xu SC, El-Sayed M, Gerig G, Correspondence Evaluation in Local Shape Analysis and Structural Subdivision, IEEE Symposium on Biomedical Imaging ISBI 2007, 1192 - 1195 3.Nain D, Styner M, Niethammer M, Levitt JJ, Shenton ME, Gerig G, Bobick A, Tannenbaum A, Statistical Shape Analysis of Brain Structures Using Spherical Wavelets, IEEE Symposium on Biomedical Imaging 2007, 209 - 212 4.Zhou C, Park DC, Styner M, Wang YM, ROI Constrained Statistical Surface Morphometry, IEEE Symposium on Biomedical Imaging ISBI 2007, 1212 - 1215 5.M. Styner, I. Oguz, S. Xu, D. Pantazis, and G. Gerig. Statistical group differences in anatomical shape analysis using hotelling T^2 metric. In Proc SPIE Vol 6512, Medical Imaging, 2007, pp. 65123Z-1 - 11. 6.Kubicki M, Styner M, Markant D, Dreusicke M, Kikinis R, McCarley R, Shenton M. Interhemispheric connectivity and schizophrenia-diffusion tensor imaging study. Schizophrenia Bulletin (2007) vol. 33 pp. 340-340 Evaluation/Validation : 7.van Ginneken B, Heimann,T, Styner M, 3D Segmentation in the Clinic: A Grand Challenge, Workshop at Medical Image Computing and Computer Assisted Intervention, MICCAI 2007, pp. 7-15, 2007.

3. National Alliance for Medical Image Computing http://na-mic.org Slicer 3 Development UNC shape analysis tool in Slicer 3 –Modules for individual steps –High level tool: select datasets and go –ToDo: QC, GLM stats, MDL support BatchMake/Condor –UNC & Kitware –Shape Analysis –Brain segmentation

4. National Alliance for Medical Image Computing http://na-mic.org Shape Analysis Collaborations: UNC, Utah, UIllinois, GT, BWH 1 IPMI, 3 ISBI, 1 SPIE and 2 clinical in prep Main research on GLM & MANCOVA support UNC Autism shape analysis: Multi-object, longitudinal New application for shape: Orthodontics Shape Differences Shape Variability Significance Maps

5. National Alliance for Medical Image Computing http://na-mic.org Cortical Correspondence Motivation: Cortical analysis of brain measures –Cortical thickness in Autism –fMRI analysis Goal: local cortical correspondence Approach: –Population based correspondence –Entropy minimization with particles on inflated surfaces –Features from original surface Sulcal depth, surface location –UNC & Utah Ensemble entropySurface entropy

6. National Alliance for Medical Image Computing http://na-mic.org Cortical Correspondence Prototype software test on 10 control datasets –Better matching of sulcal features than freesurfer –ISBI submission Next: Incorporation of additional anatomical features –Connectivity via DTI –Vessel proximity via MRA Probabilistic connectivity –MIT (Golland, Ngo)

7. National Alliance for Medical Image Computing http://na-mic.org Evaluation/Validation Tools & data for segmentation evaluation –Caudate + liver seg. –Including NAMIC data Workshop MICCAI 07 –Success, positive feedback With UUtrecht and DKFZ Continued evaluation on web: cause07.org MICCAI 08: MS lesion seg