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