Unc core 1 what did we do for na mic and or what did na mic do for us
1 / 11

- PowerPoint PPT Presentation

  • Uploaded on

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, Isabelle Corouge. UNC Contributions. Method’s Development: Shape Analysis : Set of methods / automatic complex pipelines / statistical analysis

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about '' - kato

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Unc core 1 what did we do for na mic and or what did na mic do for us l.jpg

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, Isabelle Corouge

Unc contributions l.jpg
UNC Contributions

Method’s Development:

  • Shape Analysis: Set of methods / automatic complex pipelines / statistical analysis

  • DTI Analysis: New modules / whole toolkit for tract-based analysis / atlas-based analysis / statistics

  • Close collaboration Core1/Core2 developers

  • Methods driven by clinical partners UNC/Duke and Core3

  • Key components integrated into NAMIC toolkit

    Driving biological problems:

  • Morphometric changes in schizophrenia / connectivity changes in SZ / white matter integrity in SZ

    Training/education Core5:

  • Testing/training at UNC/Duke before delivering

  • Material for DTI education: Physics/Math/Biology/Tools

  • Chapel Hill DTI Workshop

Shape analysis l.jpg

Shape Differences

Shape Variability

Significance Maps

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 analysis methods l.jpg

Φ- correspoondence coloring

Shape Analysis: Methods

  • Methods

    • 2D CC subdivision

    • Novel shape analysis

      • Hotelling T2 difference

      • FDR based correction

    • MDL curvature based shape correspondence

    • Shape Analysis Pipeline ready for clinical studies and used by NAMIC partners

    • Current integration Slicer 3

Dti quantitative analysis l.jpg


DTI: Quantitative Analysis

  • Tract-based analysis: FiberViewer:

    • User-operated tract-based analysis

    • Arc-length correspondence

    • Riemannian tensor statistics

    • Tested & applied in clinical studies

    • Journal paper submitted

  • Atlas based population studies::

    • Diffeomorphic registration

    • Voxel-wise correspondence

    • Riemannian interpol./statistics

    • Currently applied to VA DTI SZ data

  • Regional subdivision analysis (CC)

    • Currently applied to BWH/Harvard data

  • Collaboration UNC, Utah, Harvard-MIT, BWH/Harvard, Dartmouth

Dti tensor variability studies l.jpg
DTI Tensor Variability Studies

  • Study effect of MR noise on DTI measurements

  • Gradient direction schemes: Orientation invariance of FA?

  • Theory & test scans

  • UNC – Utah collaboration

  • ISMRM submission

  • Potentially important for training/education and new clinical studies

Software developments and deliverables l.jpg
Software Developments and Deliverables

  • 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 representation formats)

  • UNC promotes importance of automatic pipelines/ workflows and batch processing: large clinical studies, competitive comparison of tools, dissemination to research community

  • Early adaptation and testing of KWwidgets (KWMeshVisu, NRRD editor) and Slicer3 prototype environment (shape analysis)

What did namic do for unc l.jpg
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 between 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 labs and industry / joint collaboration with end users

Unc namic papers l.jpg


  • 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

  • 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

  • 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

  • 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

  • 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.

  • John H. Gilmore, Weili Lin, Isabella Corouge, Y. Sampath K. Vetsa, J. Keith Smith, Chaeryon Kang, Hongbin Gu, Robert M. Hamer, Jeffrey A. Lieberman, Guido Gerig Early Postnatal Development of Corpus Callosum and Corticospinal White Matter Assessed with Quantitative Tractography, submitted J. Neuroscience

  • Corpus callosum DTI abnormalities in schizophrenia, M. Kubicki, M. Shenton, G.Gerig, M. Styner, in prep.


  • 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.

  • 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

  • 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

  • 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 :

  • 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 sess. Open Source, pp. 702-705, 2006.