1. NA-MIC National Alliance for Medical Image Computing http://na-mic.org UNC Core 1: What did we do for NA-MIC and/or what did NA-MIC do for us Guido Gerig, Martin Styner, Casey Goodlett, Ipek Oguz

2. National Alliance for Medical Image Computing http://na-mic.org Shape Analysis Statistical Shape Analysis –General shape analysis framework –Shape Analysis and visualization package (3 NAMIC and 6 outside sites) –BWH/Harvard Caudate study Shape Differences Shape Variability Significance Maps

3. National Alliance for Medical Image Computing http://na-mic.org Shape Analysis: Methods Methods –2D CC subdivision –Novel shape analysis Hotelling T 2 difference FDR based correction –MDL curvature based shape correspondence –Shape Analysis Pipeline ready for clinical studies and used by NAMIC partners Φ- correspoondence coloring

4. National Alliance for Medical Image Computing http://na-mic.org DTI: Quantitative Analysis FiberViewer: –User-operated tract-based analysis –Arc-length correspondence –Riemannian tensor statistics –Tested/applied in clinical studies Atlas based analysis: –Diffeomorphic registration –Voxel-wise correspondence –Riemannian interpol./statistics –Currently applied to VA DTI SZ data Regional subdivision analysis – Corpus Callosum –Currently applied to BWH/Harvard data Collaboration UNC, Utah, Harvard-MIT, BWH/Harvard, Dartmouth Atlas

5. National Alliance for Medical Image Computing http://na-mic.org DTI Tensor Variability Studies Study effect of MR noise on DTI measurements Gradient direction schemes: Orientation invariance of FA? Theory and test scans UNC – Utah collaboration ISMRM submission

6. National Alliance for Medical Image Computing http://na-mic.org Software Developments Delivered fully functional integrated packages/pipelines composed of sets of ITK modules (Shape Analysis / DTI) Participation in efforts for standardization and interoperability (e.g., fiber bundles, NRRD, shape representations) UNC promotes importance of pipelines and batch processing for large clinical studies Early adaptation and testing of KWwidgets and Slicer3 prototype environment

7. National Alliance for Medical Image Computing http://na-mic.org What did NAMIC do for UNC? NAMIC amplifies and complements other NIH-funded UNC projects Funding of method/software development at extent difficult to fund under other grant mechanisms To learn about professional, industry-style of programming & program testing and sharing (dashboard, regression testing) NAMIC toolkit: Excellent platform to integrate, test, apply and competitively compare UNC methods and tools Impact of NAMIC on UNC Neuroimage Analysis Research: Promotes and demonstrates importance of collaborative research btw. CS and clinical partners and of sharing of tools and data NAMIC tools and standards made available and tested by our local and global non-NAMIC partners NAMIC is very attractive project for researchers and students: Exposure to multi-site, collaborative research / high visibility / contacts to research lab and industry / joint collaborations with end users

8. National Alliance for Medical Image Computing http://na-mic.org NAMIC Papers DTI: 1.Corpus callosum DTI abnormalities in schizophrenia, M. Kubicki, M. Shenton, G.Gerig, M. Styner, in preparation 2.Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis, Isabelle Corouge, P.Thomas Fletcher, Sarang Joshi, Sylvain Gouttard, Guido Gerig, Medical Image Analysis 10 (2006), 786 - 798 3.Improved Correspondence for DTI Population Studies via Unbiased Atlas Building Casey Goodlett, Brad Davis, Remi Jean, John Gilmore, and Guido Gerig, MICCAI Vol. 4191, 2006, pp. 260 - 267 4.C. Goodlett, I. Corouge, M. Jomier, and G. Gerig, A Quantitative DTI Fiber Tract Analysis Suite, The Insight Journal, vol. ISC/NAMIC/ MICCAI Workshop on Open-Source Software, 2005 5.Corouge, I., Fletcher, T., Joshi, S., Gilmore J.H., and Gerig, G., Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis, MICCAI, LNCS, Vol. 3749, 2005, pp. 131 -- 138 6.M. Styner, R. Gimpel Smith, C. Cascio, I. Oguz, M. Jomier: Corpus Callosum Subdivision based on a Probabilistic Model of Inter-hemispheric Connectivity, MICCAI, LNCS, Vol 3750, 2005 pp. 765-772. Shape: 1.M. Styner, I. Oguz, S. Xu, D. Pantazis, and G. Gerig. Statistical group differences in anatomical shape analysis using hotelling T2 metric. Proc SPIE Medical Imaging Conference, in print, 2007. 2.Oguz, Ipek, Gerig, Guido, Barre, Sebastien, Styner, Martin, A Quantitative KWMeshVisu: A Mesh Visualization Tool for Shape Analysis, 2006, ISC/NA-MIC Workshop on Open Science at MICCAI 2006, Insight Journal 3.T Heimann, I Oguz, I Wolf, M Styner, HP Meinzer, Implementing the Automatic Generation of 3D Statistical Shape Models with ITK, Open Science Workshop at MICCAI 2006, Insight Journal 4.Styner, M. and Oguz, I. and Xu, S. and Brechbuhler, C. and Pantazis, D. and Levitt, J. and Shenton, M. and Gerig, G.:Framework for the Statistical Shape Analysis of Brain Structures using SPHARM-PDM, Open Science Workshop at MICCAI 2006, Insight Journal Software Development : 1.Martin Styner, Matthieu Jomier, and Guido Gerig, Closed and open source neuroimage analysis tools and libraries at UNC, in IEEE International Symposium on Biomedical Imaging (ISBI), special session Open Source, pp. 702-705, Apr. 2006.