Difference between revisions of "ProstateSegmentationAHM2009"

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<h1>Objective</h1>
 
<h1>Objective</h1>
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For the task of prostate segmentation, we provide two tools: 1. shape based and 2. semi-automatic random walk based. The goal is to put both algorithm into Slicer3 as command line modules.
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For the task of prostate segmentation, we provide two tools: 1. shape based and 2. semi-automatic random walk based. The goal is to put both algorithm into Slicer3.
  
 
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<h1>Approach, Plan</h1>
 
<h1>Approach, Plan</h1>
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Algorithm 1. is a Bayesian Shape based segmentation. The shape of prostates are learned and then the new image is segmented using the shapes learned. Algorithm 2. is based on the Random Walks segmentation algorithm. It need more human input but the result could be interactively improved arbitrarily close to user's expectation.
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Algorithm 1. is a Shape based segmentation. The shape of prostates are learned and then the new image is segmented using the shapes learned. Algorithm 2. is based on the Random Walks segmentation algorithm. It need more human input but the result could be interactively improved arbitrarily close to user's expectation.
  
 
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<h1>Progress</h1>
 
<h1>Progress</h1>
  
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Algorithm 2. is already in the form of command line module. Algorithm 1. is also ready to be ported in.
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During the project week, we achieved:
  
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The objectives for the project week are
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* Integrated semi-auto algorithm (algorithm 2) into Trans Rectal Prostate biopsy interactive loadable module, shown in the middle figure above.
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1. Integrate algorithm 2 (which is currently a command line module) into Trans Rectal Prostate biopsy interactive loadable module
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* Integrated shape based algorithm (algorithm 1) into Slicer3 as command line module, shown in the right figure above.
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2. Create a command line module for algorithm 1.
 
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3. Improve the algorithm for better segmentation performance.
 
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Objective 1 achieved: We have integrated Algorithm 2 (random walk segmentation) inside the interactive loadable module Trans rectal prostate biopsy module
 
 
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Latest revision as of 23:42, 8 January 2009

Home < ProstateSegmentationAHM2009
Return to Project Week Main Page
Prostate segmentation integrated inside TR Prostate biopsy interactive module
Shape base prostate segmentation in Slicer through command line module



Key Investigators

  • Gabor Fichtinger, Purang Abolmaesumi, David Gobbi, Siddharth Vikal; Queen’s University
  • Allen Tannenbaum, Yi Gao; Georgia Tech
  • Katie Hayes, Brigham and Women's Hospital


Objective

For the task of prostate segmentation, we provide two tools: 1. shape based and 2. semi-automatic random walk based. The goal is to put both algorithm into Slicer3.

Approach, Plan

Algorithm 1. is a Shape based segmentation. The shape of prostates are learned and then the new image is segmented using the shapes learned. Algorithm 2. is based on the Random Walks segmentation algorithm. It need more human input but the result could be interactively improved arbitrarily close to user's expectation.

Progress

During the project week, we achieved:

  • Integrated semi-auto algorithm (algorithm 2) into Trans Rectal Prostate biopsy interactive loadable module, shown in the middle figure above.
  • Integrated shape based algorithm (algorithm 1) into Slicer3 as command line module, shown in the right figure above.


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