Difference between revisions of "2012 Summer Project Week:RidgeExtractionAtrialWallSegmentation"

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Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
 
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
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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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Image:MRI1.jpg|Example of manual segmentation of the left atrial wall.  
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Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
 
 
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==Background==
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Catheter ablation has been proposed for treatment of atrial fibrillation arrhythmia. MRI data is used to explore lesion ablation and scarification locations are extracted from MRI image data. In addition, MRI analysis may help to predict if the ablation procedure will help a patient.
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Many of these image analysis tasks are largely based on segmentation of left atrial wall, which is done manually or semi-automatically.
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Automatic segmentation uses moving contours or surfaces (interfaces) to segment image data by minimizing a predefined energy function.
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These moving interfaces are highly affected by image data, which can be thought as a force field pushing the interface to the features of choice. Thus, the choice of image features attracting the interface is critical.
  
 
==Key Investigators==
 
==Key Investigators==
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<h3>Objective</h3>
 
<h3>Objective</h3>
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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 exploring different image features which are appropriate for automatic segmentation. Our objective is to compare different topological extrema ranking algorithms (including maximum persistence and perceptual ridge importance) to provide the most appropriate features, based on expert's manual segmentation.
  
  
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
  
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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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* Implementing the comparison framework
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* Ellipsoidal MRI transform
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* Local ridge extraction
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* Topological persistence algorithm implementation
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* Comparison of different topological simplification approaches using the comparison framework
  
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Our plan for the project week is to first try out <bar>,...
 
  
 
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<h3>Progress</h3>
 
<h3>Progress</h3>
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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.
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We have developed topological simplification methods for removing noisy local maxima. The resulting ridge detection algorithm shows average error less then 2 pixels compared to the manual segmentation.  
  
  
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==Delivery Mechanism==
 
==Delivery Mechanism==
  
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This work will be delivered to the NA-MIC Kit as a
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This work will be delivered to the NA-MIC Kit as an Extension -- commandline  
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#ITK Module
 
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#Slicer Module
 
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##Built-in
 
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##Extension -- commandline - YES
 
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##Extension -- loadable
 
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#Other (Please specify)
 
  
 
==References==
 
==References==
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*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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* 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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* 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.
 
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* 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 . -->
 

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