Difference between revisions of "Slicer-IGT/GPU-IGT/112707"

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# Introduction of members of this project
 
# Introduction of members of this project
 
* Nicholas: student from Tokyo  
 
* Nicholas: student from Tokyo  
* Benjamin: student from ETH, be at SPL for 6 mo. till May 31, 2007. Experience in golfing simulator, histoscopy simulator, open-source game software. His project here is GPU accelerated Slicer for 4D IGT.  
+
* Benjamin: student from ETHZ, be at SPL for 6 mo. till May 31, 2008. Experience in golfing simulator, histoscopy simulator, open-source game software. His project here is GPU accelerated Slicer for 4D IGT.  
  
  
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[[Image:RigidReg.jpg]]  
 
[[Image:RigidReg.jpg]]  
  
Rigid registration using affine transformation, MI similarity measure, and Powell optimization method impletented on CUDA platform. GPU-acceleration was performed on affine transformation and MI similarity measure. Performance boost of around x12 was achieved.
+
Rigid registration using affine transformation, MI similarity measure, and Powell optimization method implemented on CUDA platform. GPU-acceleration was performed on affine transformation and MI similarity measure. Performance boost of around x12 was achieved.
* Non-rigid registration (also Japanese cas paper)
+
* Non-rigid registration (also Japanese CAS paper)
 
[[Image:NonrigidReg.jpg]]  
 
[[Image:NonrigidReg.jpg]]  
  
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*CUDA calculator
 
*CUDA calculator
 
*8800GTX, 8800GTS, Quadro FX5600, Tesla C870 is CUDA 1.0 compatible
 
*8800GTX, 8800GTS, Quadro FX5600, Tesla C870 is CUDA 1.0 compatible
*8600GTS, 8800GT is CUDA 1.1 compatible which comes with Atomic function to control cuncurrent access to memoery from multiple thread
+
*8600GTS, 8800GT is CUDA 1.1 compatible which comes with Atomic function to control concurrent access to memory from multiple thread
  
 
# Extension to ITK
 
# Extension to ITK
 
* CMake turn on/off #DEFINE
 
* CMake turn on/off #DEFINE
* VTK VolumePro as part of volume redering
+
* VTK VolumePro as part of volume rendering
 
* ITK parallelized process  
 
* ITK parallelized process  
* [Action items, Nichoals] Mid-term goal for Nicholas is to port his rigid and non-rigid regstration to ITK
+
* [Action items, Nicholas] Mid-term goal for Nicholas is to port his rigid and non-rigid registration to ITK
 
* [Action items, Nicholas] Contact Utah team hear how exactly they implement their ITK.
 
* [Action items, Nicholas] Contact Utah team hear how exactly they implement their ITK.
 
* [Action items, Nicholas] sending volume rendering code by Dec. 6th.
 
* [Action items, Nicholas] sending volume rendering code by Dec. 6th.
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* CUDA accelerated volume rendering
 
* CUDA accelerated volume rendering
 
* x15 - 20 improvement
 
* x15 - 20 improvement
* comparison to other people's CG-based volume rendering [[media:SIGGRAPH-GPU.pdf]]
+
* [[media:SIGGRAPH-GPU.pdf|comparison to other people's CG-based volume rendering]]
 
* [Action items, Benjamin] port CUDA-based volume rendering to vtk volume rendering classes, and then to Slicer
 
* [Action items, Benjamin] port CUDA-based volume rendering to vtk volume rendering classes, and then to Slicer
* [Action items, Benjamin] succeed Nicholas' itk-cuda-rigid non-rigid regstration and port them to Slicer in the context of MRg cardiac ablation
+
* [Action items, Benjamin] succeed Nicholas' itk-cuda-rigid non-rigid registration and port them to Slicer in the context of MRg cardiac ablation
  
 
# Timeline
 
# Timeline

Revision as of 15:05, 19 May 2008

Home < Slicer-IGT < GPU-IGT < 112707
  1. Introduction of members of this project
  • Nicholas: student from Tokyo
  • Benjamin: student from ETHZ, be at SPL for 6 mo. till May 31, 2008. Experience in golfing simulator, histoscopy simulator, open-source game software. His project here is GPU accelerated Slicer for 4D IGT.


  1. Nicholas update on his CUDA project
  • Rigid and non-rigid registration using CUDA using Nvidia 8800 GTX (350GFlps) compatible with CUDA platform.
  • Rigid registration (Japanese cas paper)

RigidReg.jpg

Rigid registration using affine transformation, MI similarity measure, and Powell optimization method implemented on CUDA platform. GPU-acceleration was performed on affine transformation and MI similarity measure. Performance boost of around x12 was achieved.

  • Non-rigid registration (also Japanese CAS paper)

NonrigidReg.jpg

Non-rigid registration using Rueckert's B-spline algorithm. Performance boost of around x10-x20 was achieved.

  1. Tool kit used
  • CUDA calculator
  • 8800GTX, 8800GTS, Quadro FX5600, Tesla C870 is CUDA 1.0 compatible
  • 8600GTS, 8800GT is CUDA 1.1 compatible which comes with Atomic function to control concurrent access to memory from multiple thread
  1. Extension to ITK
  • CMake turn on/off #DEFINE
  • VTK VolumePro as part of volume rendering
  • ITK parallelized process
  • [Action items, Nicholas] Mid-term goal for Nicholas is to port his rigid and non-rigid registration to ITK
  • [Action items, Nicholas] Contact Utah team hear how exactly they implement their ITK.
  • [Action items, Nicholas] sending volume rendering code by Dec. 6th.
  1. Volume rendering
  • CUDA accelerated volume rendering
  • x15 - 20 improvement
  • comparison to other people's CG-based volume rendering
  • [Action items, Benjamin] port CUDA-based volume rendering to vtk volume rendering classes, and then to Slicer
  • [Action items, Benjamin] succeed Nicholas' itk-cuda-rigid non-rigid registration and port them to Slicer in the context of MRg cardiac ablation
  1. Timeline
  • NH will write paper on IV-CUDA rendering for Journal
  • Hata suggested publication of ITK-CUDA registration in Insight Journal (Feb)
  • Benjamin will have short summery as of March 15 for MICCAI.
  • Benjamin will finish his project by May 15th.
  • Benjamin
  1. Communication

Bi-weekly t-con to update each other week. Next one is Dec 11, 2007 at 9am.