Difference between revisions of "2013 Winter Project Week Gyne Brachy"

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<h3>Objective</h3>
 
<h3>Objective</h3>
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* We are developing methods for identifying scar tissue from CARMA data. Our previous method demonstrates an effective identification ability for DE-MRI data. In this method, the intensity distribution inside the LA myocardial wall is modeled as a mixture of Gaussians. To improve the performance of this method, we will integrate the intensity information from the LA chamber into the overall identification procedure.
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* The [http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/Extensions/iGyne iGyne] module is a user friendly Slicer module which is designed to assist gynecologic radiation oncologists in the process of applicator placement and brachytherapy needle insertion. Currently the module can perform applicator registration and needle segmentation and labeling successfully.
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* We will discuss possible improvements for scar identification.  
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* The objective of this project is to develop a method to validate and measure the accuracy of the needle segmentation results.  
 
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
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* Design an identification scheme using the LA intensity as a prior
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* Needle digitization and exporting the segmented results.
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* Test the method using CARMA data
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* Comparison of the needle segmentation results from MRI images with the Post-operation CT checking images.
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* Deliver the implementation in CLI module.
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* Define metrics to measure the accuracy of the segmentation results.
 
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Revision as of 16:23, 7 January 2013

Home < 2013 Winter Project Week Gyne Brachy

Key Investigators

  • Alireza Mehrtash, BWH
  • Csaba Pinter, Queen's

Project Description

Objective

  • The iGyne module is a user friendly Slicer module which is designed to assist gynecologic radiation oncologists in the process of applicator placement and brachytherapy needle insertion. Currently the module can perform applicator registration and needle segmentation and labeling successfully.
  • The objective of this project is to develop a method to validate and measure the accuracy of the needle segmentation results.

Approach, Plan

  • Needle digitization and exporting the segmented results.
  • Comparison of the needle segmentation results from MRI images with the Post-operation CT checking images.
  • Define metrics to measure the accuracy of the segmentation results.

Progress

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