|
|
| (6 intermediate revisions by the same user not shown) |
| Line 1: |
Line 1: |
| | __NOTOC__ | | __NOTOC__ |
| − | <gallery>
| + | [[File:Tract cloud.jpg|600px|thumb|left|tract cloud]] |
| − | Image:PW-SLC2010.png|[[2010_Winter_Project_Week#Projects|Projects List]]
| |
| − | Image:genuFAp.jpg|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.
| |
| − | Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
| |
| − | </gallery>
| |
| | | | |
| | ==Key Investigators== | | ==Key Investigators== |
| − | * UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig | + | * Previously: Julien von Siebenthal |
| − | * Utah: Tom Fletcher, Ross Whitaker | + | * BWH: Andrew Rausch, Marek Kubicki |
| − | | |
| − | <div style="margin: 20px;">
| |
| − | <div style="width: 27%; float: left; padding-right: 3%;">
| |
| | | | |
| | <h3>Objective</h3> | | <h3>Objective</h3> |
| − | We are developing methods for analyzing diffusion tensor data along fiber tracts. The goal is to be able to make statistical group comparisons with fiber tracts as a common reference frame for comparison.
| + | Julien has kindly updated his stochastic tractography algorithm in the Python Stochastic Tractography module in Slicer 3.5. It needs to be tested and verified as working. |
| − | | |
| − | | |
| − | | |
| − | | |
| − | | |
| − | | |
| − | </div>
| |
| − | | |
| − | <div style="width: 27%; float: left; padding-right: 3%;">
| |
| − | | |
| − | <h3>Approach, Plan</h3>
| |
| − | | |
| − | Our approach for analyzing diffusion tensors is summarized in the IPMI 2007 reference below. The main challenge to this approach is <foo>.
| |
| − | | |
| − | Our plan for the project week is to first try out <bar>,...
| |
| − | | |
| − | </div>
| |
| − | | |
| − | <div style="width: 40%; float: left;">
| |
| − | | |
| − | <h3>Progress</h3>
| |
| − | 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 [[NA-MIC/Projects/Diffusion_Image_Analysis/DTI_Software_and_Algorithm_Infrastructure|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.
| |
| − | | |
| − | | |
| − | </div>
| |
| − | </div>
| |
| − | | |
| − | <div style="width: 97%; float: left;">
| |
| − | | |
| − | ==References==
| |
| − | *Fletcher P, Tao R, Jeong W, Whitaker R. [http://www.na-mic.org/publications/item/view/634 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. [http://www.na-mic.org/publications/item/view/292 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. [http://www.na-mic.org/publications/item/view/1122 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 .
| |
| | | | |
| − | </div>
| + | Andrew is currently updating the tutorial for this new method. Current progress can be found here: [[File:Stochastic Jan09.ppt| stochastic tutorial powerpoint]] |
