Difference between revisions of "2013 Summer Project Week:SegmentationAidedRegistration"

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Image:PW-MIT2013.png|[[2013_Summer_Project_Week#Projects|Projects List]]
 
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Image:FibrosisPval20130526.png|p-value between DCE-MRI between cured patiens and AFib recurrent patient.
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Image:AfibBeforeRegistrationSmall.png|Two images (3D) to be registered.
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Image:AfibSegmentationAidedRegistration.png|Segmentation aided registration using this module.
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Image:AfibSegmentationAidedRegistrationContour.png|Segmentation aided registration using this module, with red contour of left atrium.
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Image:AfibMIAffineRegistrationWithContour.png|MI registration.
 
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<h3>Objective</h3>
 
<h3>Objective</h3>
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Among the AFib patients underwent RF ablation, the relative high AFib recurrence rate is a concern. The correlation between the cure/recurrence ratio with the distribution of the fibrosis would provide insight on the disease assessment and treatment planning.
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When registering two images, sometime we want some specific regions in the two images to be particularly accurately matched.
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
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The fibrosis distributions on the left atrium wall is imaged using the dynamic contrast enhanced MRI. Distributed on different anatomical structures, they are considered as "mass" defined on different domains. Under the framework of the optimal mass transport (OMT), the masses are transported to a common domain where the statistical analysis can then be applied. The significant different regions are then characterized by the low-p-value regions.
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We use the segmentation of the target region to aided the registration.
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<h3>Progress</h3>
 
<h3>Progress</h3>
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C++ code using ITK and VTK is finished.
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Extension in nightly build. Can be installed from Extension manager.
  
  
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==Delivery Mechanism==
 
==Delivery Mechanism==
  
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This work will be delivered to the NA-MIC Kit as a commandline extension.
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This work has been delivered to the NA-MIC Kit as a commandline extension. See module page at:
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https://www.slicer.org/wiki/Documentation/Nightly/Modules/SegmentationAidedRegistration
  
 
==References==
 
==References==
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* Y Gao, Y Rathi, S Bouix, A Tannenbaum; ''Filtering in the Diffeomorphism Group and the Registration of Point Sets''; IEEE Transactions on Image Processing 21 (10), 4383--4396
 
* [http://www.na-mic.org/Wiki/index.php/DBP3:Utah Utah DBP]
 
* [http://www.na-mic.org/Wiki/index.php/DBP3:Utah Utah DBP]
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* Y. Gao and S. Bouix, “Synthesis of realistic subcortical anatomy with known surface deformations,” in MICCAI Workshop on Mesh Processing in Medical Image Analysis, 2012, pp. 80–88.
 
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* T. Riklin-Raviv, Y. Gao, J. Levitt, and S. Bouix, “Statistical shape analysis for population studies via level-set based shape morphing,” in ECCV Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment, 2012, pp. 42–51.
 

Latest revision as of 18:07, 10 July 2017

Home < 2013 Summer Project Week:SegmentationAidedRegistration

  • Two images (3D) to be registered.

  • Segmentation aided registration using this module.

  • Segmentation aided registration using this module, with red contour of left atrium.

  • MI registration.


Key Investigators

  • Yi Gao, LiangJia Zhu, Josh Cates, Rob MacLeod, Sylvain Bouix, Ron Kikinis, Allen Tannenbaum

Objective

When registering two images, sometime we want some specific regions in the two images to be particularly accurately matched.

Approach, Plan

We use the segmentation of the target region to aided the registration.

Progress

Extension in nightly build. Can be installed from Extension manager.


Delivery Mechanism

This work has been delivered to the NA-MIC Kit as a commandline extension. See module page at: https://www.slicer.org/wiki/Documentation/Nightly/Modules/SegmentationAidedRegistration

References

  • Y Gao, Y Rathi, S Bouix, A Tannenbaum; Filtering in the Diffeomorphism Group and the Registration of Point Sets; IEEE Transactions on Image Processing 21 (10), 4383--4396
  • Utah DBP
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