NA-MICNational Alliance for Medical Image Computing http://na-mic.org
Shape Analysis and Cortical Correspondence
Martin Styner
Core 1 (Algorithms), UNCIpek Oguz, Xavier Barbero, Nicolas Augier
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 2007Shape: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 - 11953. 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.
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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
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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
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 entropy Surface entropy
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)
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