Difference between revisions of "2009 Summer Project Week Cone Beam backprojection"

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==Key Investigators==
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Key Investigators==
 
* U Michigan: Zhou Shen, Jeff Fessler, James Balter
 
* U Michigan: Zhou Shen, Jeff Fessler, James Balter
 
* MGH: Greg Sharp, Rui Li
 
* MGH: Greg Sharp, Rui Li
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<h3>Progress</h3>
 
<h3>Progress</h3>
To be filled in later.
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The Sharp/Shackelford code and demo was successfully compiled.  Following, a QT-developed interface from Zhou Shen was modified to use this backprojector.  Ramp filtering is still needed (example is unsharp mask post processing), but the current interface prrovides a flexible tool for using and modifying Varian projections for research investiations.
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Image:shots1.png
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example cone beam projection
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Image:shots3.png
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example reconstructed axial image (no ramp filter but unsharp masked)
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The Fessler feldkamp backprojection demo was successfully compiled in Matlab and partially accelerated in CUDA using the Accelereyes product.
  
  

Latest revision as of 01:30, 26 June 2009

Home < 2009 Summer Project Week Cone Beam backprojection

Key Investigators==

  • U Michigan: Zhou Shen, Jeff Fessler, James Balter
  • MGH: Greg Sharp, Rui Li
  • NVIDIA: Joe Stam


Objective

We will be providing infrastructure for investigation of modifications to cone beam Ct reconstruction methods to support future research in image-guided radiation therapy (IGRT)




Approach, Plan

A commmonly used algorithm for Cone Beam CT reconstruction is the Feldkamp backprojection method. We plan to implement this in CUDA to evaluate the speed, and wrap it into an interface that will accept as input Varian Cone Beam CT projection images,

Progress

The Sharp/Shackelford code and demo was successfully compiled. Following, a QT-developed interface from Zhou Shen was modified to use this backprojector. Ramp filtering is still needed (example is unsharp mask post processing), but the current interface prrovides a flexible tool for using and modifying Varian projections for research investiations.

The Fessler feldkamp backprojection demo was successfully compiled in Matlab and partially accelerated in CUDA using the Accelereyes product.