Difference between revisions of "2011 Winter Project Week:LandmarkRegularization"

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__NOTOC__
 
__NOTOC__
 
<gallery>
 
<gallery>
Image:PW-SLC2011.png|[[2011_Winter_Project_Week#Projects|Projects List]]
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File:na-mic0.png|Slecer 3.6 panel
Image:genuFAp.jpg|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.
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File:na-mic1.png|Input reference image
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
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File:na-mic2.png|Input test image
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File:na-mic3.png|Output warped image
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</gallery>
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<gallery>
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File:na-mic4.png|Input reference image
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File:na-mic5.png|Input test image
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File:na-mic6.png|Output warped image without regularization
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File:na-mic7.png|Output warped image with regularization
 
</gallery>
 
</gallery>
  
==Instructions for Use of this Template==
 
#Please create a new wiki page with an appropriate title for your project using the convention Project/<Project Name>
 
#Copy the entire text of this page into the page created above
 
#Link the created page into the list of projects for the project event
 
#Delete this section from the created page
 
#Send an email to tkapur at bwh.harvard.edu if you are stuck
 
  
 
==Key Investigators==
 
==Key Investigators==
* UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
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*MGH: Nadya Shusharina, Gregory Sharp
* Utah: Tom Fletcher, Ross Whitaker
 
  
 
<div style="margin: 20px;">
 
<div style="margin: 20px;">
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<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.
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We are introducing a new method for local enhancement of image registration. The method is intended to make rapid, interactive corrections of local registration failures with a small number of mouse clicks.
 
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We use Gaussian radial basis functions (RBFs)
 
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to define a vector field from point landmarks,
 
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and apply regularization based on the vector field second order derivative. 
 
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</div>
 
</div>
  
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<h3>Approach, Plan</h3>
 
<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>.
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Our approach is based on the fact that the Gaussian RBF has infinite support, but the influence of each
 +
RBF is localized, making this method well suited for local corrections.
 +
In addition, Gaussian RBFs have a distinct advantage over competing
 +
approaches such as Wendland functions, because the
 +
regularized vector field can be solved exactly with a simple equation.
 +
Algorithm for the landmark-based registration has been implemented as a part of out in-house software Plastimatch. We have validated the method on 10 large landmark sets. This work has been submitted for publication to IEEE Transactions on Medical Imaging.  
  
Our plan for the project week is to first try out <bar>,...
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Our plan for the project week is to implement our registration algorithm as a Slicer command line module.
  
 
</div>
 
</div>
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<h3>Progress</h3>
 
<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.
 
 
  
 +
We have implemented LANDWARP Landmark deformable registration command line module. It appears under All modules/Plastimatch as Input/Output panel. There you choose Fixed Volume which is a reference image, Moving Volume which is a test image that will be warped to match the reference image. You also choose Fixed Fiducials and Moving Fiducials which are fidicial lists you created for reference and test image respectively. Output Volume is where the warped image will be placed (you can create new or overwrite existing image). Then you can choose a type of landmark based algorithm, "tps" for global registration or "gauss" for local registration. Local registration requires RBF radius, Stiffness and Default Pixel Value which by default are 50 mm, 0, and -1000, respectively. After you click Apply button and wait until registration is done, the warped image will appear automatically in Slicer window.
 
</div>
 
</div>
 
</div>
 
</div>
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#Slicer Module
 
#Slicer Module
 
##Built-in
 
##Built-in
##Extension -- commandline
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##Extension -- commandline YES
 
##Extension -- loadable
 
##Extension -- loadable
 
#Other (Please specify)
 
#Other (Please specify)
  
 
==References==
 
==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.
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*DIR-LAB. http://www.dir-lab.com
* 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.
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*Plastimatch. http://plastimatch.org
* 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>
 
</div>

Latest revision as of 15:31, 14 January 2011

Home < 2011 Winter Project Week:LandmarkRegularization


Key Investigators

  • MGH: Nadya Shusharina, Gregory Sharp

Objective

We are introducing a new method for local enhancement of image registration. The method is intended to make rapid, interactive corrections of local registration failures with a small number of mouse clicks. We use Gaussian radial basis functions (RBFs) to define a vector field from point landmarks, and apply regularization based on the vector field second order derivative.

Approach, Plan

Our approach is based on the fact that the Gaussian RBF has infinite support, but the influence of each RBF is localized, making this method well suited for local corrections. In addition, Gaussian RBFs have a distinct advantage over competing approaches such as Wendland functions, because the regularized vector field can be solved exactly with a simple equation. Algorithm for the landmark-based registration has been implemented as a part of out in-house software Plastimatch. We have validated the method on 10 large landmark sets. This work has been submitted for publication to IEEE Transactions on Medical Imaging.

Our plan for the project week is to implement our registration algorithm as a Slicer command line module.

Progress

We have implemented LANDWARP Landmark deformable registration command line module. It appears under All modules/Plastimatch as Input/Output panel. There you choose Fixed Volume which is a reference image, Moving Volume which is a test image that will be warped to match the reference image. You also choose Fixed Fiducials and Moving Fiducials which are fidicial lists you created for reference and test image respectively. Output Volume is where the warped image will be placed (you can create new or overwrite existing image). Then you can choose a type of landmark based algorithm, "tps" for global registration or "gauss" for local registration. Local registration requires RBF radius, Stiffness and Default Pixel Value which by default are 50 mm, 0, and -1000, respectively. After you click Apply button and wait until registration is done, the warped image will appear automatically in Slicer window.

Delivery Mechanism

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

  1. ITK Module
  2. Slicer Module
    1. Built-in
    2. Extension -- commandline YES
    3. Extension -- loadable
  3. Other (Please specify)

References