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

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# Nicholas update on his CUDA project
 
# Nicholas update on his CUDA project
 
* Rigid and non-rigid registration using CUDA using Nvidia 8800 GTX (350GFlps) compatible with CUDA platform.
 
* Rigid and non-rigid registration using CUDA using Nvidia 8800 GTX (350GFlps) compatible with CUDA platform.
* Rigid registration (Japanese cas paper) *******to be filled by Nicholas ****** x12
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* Rigid registration (Japanese cas paper)  
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[[Image:RigidReg.jpg]]
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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.
 
* Non-rigid registration based on (Rueckert et al.). achieved x10-x20  
 
* Non-rigid registration based on (Rueckert et al.). achieved x10-x20  
  
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* [Action items, Nichoals] Mid-term goal for Nicholas is to port his rigid and non-rigid regstration to ITK
 
* [Action items, Nichoals] Mid-term goal for Nicholas is to port his rigid and non-rigid regstration 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.
* [Actoinj items, Nicholas] sending volume rendering code by Dec. 6th.
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* [Action items, Nicholas] sending volume rendering code by Dec. 6th.
  
 
# Volume rendering
 
# Volume rendering

Revision as of 14:18, 6 December 2007

Home < Slicer-IGT < GPU-IGT < 112707
  1. Introduction of members of this project
  • 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.


  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 impletented on CUDA platform. GPU-acceleration was performed on affine transformation and MI similarity measure. Performance boost of around x12 was achieved.

  • Non-rigid registration based on (Rueckert et al.). achieved x10-x20
  1. Tool kit used
  • CUDA calculator
  • 8800GTX is CUDA 1.0 compatible
  • XXXX is CUDA 1.1 compatible which comes with Atomic function to control cuncurrent access to memoery from multiple thread
  1. Extension to ITK
  • CMake turn on/off #DEFINE
  • VTK VolumePro as part of volume redering
  • 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] 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 media:SIGGRAPH-GPU.pdf
  • [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
  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.