Difference between revisions of "Project Week 25/NeedleSegmentation"

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* Refine/clear the segmentations coming from the CNN algorithm.
 
* Refine/clear the segmentations coming from the CNN algorithm.
* Figure out how to transfer MRIs to a server hosting the CNN code and how to get back the results.
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* Figure out how to transfer MRIs to a server hosting the CNN code and get back the results.
 
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* Clustering and morphological filter for data cleaning.
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* Clustering and morphological filters for data cleaning.
* Talk with someone of core team to figure out how to remotely process the data.  
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* Talk with someone from the core team to figure out how to remotely process the data.  
 
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Revision as of 15:09, 22 June 2017

Home < Project Week 25 < NeedleSegmentation


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Key Investigators

Project Description

NeedleFinder offers tools to segment needles from MRI/CT. It has mostly been tested on MRI from GYN brachytherapy cases. Anyway, this tool requires manual interaction. Now we want to develop a completely automatic strategy to segment the needles. For this purpose, we tested a CNN approach that provides good results, even if a post processing step must be implemented in order to remove some noise and to refine the obtained segmentations.

Objective Approach and Plan Progress and Next Steps
  • Refine/clear the segmentations coming from the CNN algorithm.
  • Figure out how to transfer MRIs to a server hosting the CNN code and get back the results.
  • Clustering and morphological filters for data cleaning.
  • Talk with someone from the core team to figure out how to remotely process the data.

TDB

Illustrations

home_cropped.jpg

Background and References

  1. NeedleFinder website
  2. Model-based Catheter Segmentation in MRI-images