Difference between revisions of "Projects:ShapeCorrespondence UNCOrthoApp"
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Revision as of 18:42, 8 June 2009
Home < Projects:ShapeCorrespondence UNCOrthoApp
Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.
Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
EDITED Trying to add more images into the current layout.
This template page is under construction, read under your risk and responsibility :P
Instructions for Use of this Template
- EDITED EDITED EDITED EDITED EDITED EDITED EDITED EDITED EDITED EDITED EDITED EDITED EDITED EDITED EDITED
- Link the created page into the list of projects for the project event TO DO!!
- Delete this section from the created page TO DO!!
- Send an email to tkapur at bwh.harvard.edu if you are stuck
Key Investigators
- UNC: Beatriz Paniagua, Martin Styner, Lucia Cevidanes
Objective
We are developing methods for analyzing the possible application of Shape Correspondence to Orthodontic applications. Three projects are currently in progress:
- Temporomandibular Joint (TMJ) Osteoarthritis (OA). Blablablabla... disease characterization and treatment planing
- Asymmetry. Blablablabla... surgery planning.
- Skeletodental deformities corrective surgery. Blablablabla stability testing, simulation lilili.
Approach, Plan
Our approach for lalala is lalala. The main challenge this approach is lots of pre-processing are needed to adapt the current methods to the new data (until now, Shape Correspondence applied almost entirely to brain morphometry studies).
Our plan for the project week is to first try out hmmmm After correspondence, statistical analysis... Integration of the UNC statistical core to Slicer 3!<bar>,...
Progress
Software for the fiber tracking and statistical analysis along the tracts has been implemented. The statistical methods for diffusion tensors are implemented as ITK code as part of the DTI Software Infrastructure project. The methods have been validated on a repeated scan of a healthy individual. This work has been published as a conference paper (MICCAI 2005) and a journal version (MEDIA 2006). Our recent IPMI 2007 paper includes a nonparametric regression method for analyzing data along a fiber tract.
References
- Fletcher P, Tao R, Jeong W, Whitaker R. A volumetric approach to quantifying region-to-region white matter connectivity in diffusion tensor MRI. Inf Process Med Imaging. 2007;20:346-358. PMID: 17633712.
- Corouge I, Fletcher P, Joshi S, Gouttard S, Gerig G. Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis. Med Image Anal. 2006 Oct;10(5):786-98. PMID: 16926104.
- Corouge I, Fletcher P, Joshi S, Gilmore J, Gerig G. Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis. Int Conf Med Image Comput Comput Assist Interv. 2005;8(Pt 1):131-9. PMID: 16685838.
- Goodlett C, Corouge I, Jomier M, Gerig G, A Quantitative DTI Fiber Tract Analysis Suite, The Insight Journal, vol. ISC/NAMIC/ MICCAI Workshop on Open-Source Software, 2005, Online publication: http://hdl.handle.net/1926/39 .
