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Generation of planar radiographs from 3D
   anatomical models using the GPU
             André dos Santos Cardoso
               Supervisor: Jorge M. G. Barbosa




                      University of Porto
         Faculty of Engineering of University of Porto
               andre.cardoso@fe.up.pt, jbarbosa@fe.up.pt




                         May 10, 2010



       André dos Santos Cardoso       DRR Generation       1 / 11
Contents

 1   Introduction
        Context Overview
        Project’s Objective

 2   State of the Art

 3   Detailed Objectives
       Technologies

 4   Work Plan

 5   Bibliography



                 André dos Santos Cardoso   DRR Generation   2 / 11
Context Overview



   Digitally Reconstructed Radiographs
   (DRRs)
       Taking a radiography from 3D digital
       anatomical models – vertebrae models
       in this case
       Form of depth peeling, using
       ray-casting
   Key component in 2D/3D registration
   process




              André dos Santos Cardoso   DRR Generation   3 / 11
Context Overview
    DRRs are taken from vertebrae models built with 3D
    meshes
        DRR generation as mean to validate and/or correct the
        reconstructed 3D models
            Vertebrae Shape Recovery Using 2D/3D Non-Rigid
            Registration
        Important techniques for Scoliosis treatment and follow-ups
            Volume recovery using Biplanar Radiography Techniques
            Alternatives to MRIs and CTs




             André dos Santos Cardoso   DRR Generation                4 / 11
Project’s Objective



Build Fast DRR Algorithms
   DRR calculation is a bottleneck
       3D reconstruction usage in a
       daily basis requires high
       performances
   Take advantage of processing
   power of new GPUs
       Common workstations could do
       the job!




              André dos Santos Cardoso   DRR Generation   5 / 11
State of the Art


     Algorithms are variations of depth peeling using ray-casting,
     and attenuation law for bone material
     Few Applications of DRR to 3D Meshes (most work on CT
     data – voxels)
     Using OpenGL Shading Language (GLSL)
         Multi Pass Algorithm is available
         Single Pass Algorithm is considered the state of the art, but
         no applied implementation exists
     Compute Unified Device Architecture (CUDA) peeling
     examples exist (no DRR examples)




              André dos Santos Cardoso   DRR Generation                  6 / 11
Detailed Objectives



   Enhance the existing solution

       Implement Single Pass Algorithm using
       GLSL Technology
       Implement Single Pass Algorithm using
       CUDA Technology

       Compare and evaluate attained
       solutions with existing approaches




              André dos Santos Cardoso   DRR Generation   7 / 11
Technologies
    C/C++ programming using OpenGL and CUDA
        Intended solution working both on Windows and *nix systems
        Visual Studio 2008 / Vim :)
        Possible packaging of solution as open-source library
    GLSL is part of the OpengGL standard
        provides mechanism to change graphics pipeline, using
        shaders
    CUDA is a Nvidia proprietary technology
        Nvidia’s CUDA SDK provides C/C++ extensions to execute
        paralell code directly on the GPU




             André dos Santos Cardoso   DRR Generation               8 / 11
Work Plan




            André dos Santos Cardoso   DRR Generation   9 / 11
Thank You for Listening!
                    Ask Away!




    André dos Santos Cardoso   DRR Generation   10 / 11
Bibliography
   Cass Everitt.
   Interactive order-independent transparency.
   NVIDIA OpenGL Applications Engineering. 05/15/2001. Accessed in April 29, 2010.
   http://developer.nvidia.com/object/Interactive_Order_Transparency.html.
   Fang Liu, Meng-Cheng Huang, Xue-Hui Liu, and En-Hua Wu.
   Freepipe: a programmable parallel rendering architecture for efficient multi-fragment effects.
   In I3D ’10: Proceedings of the 2010 ACM SIGGRAPH symposium on Interactive 3D Graphics and Games,
   pages 75–82, New York, NY, USA, 2010. ACM.
   A. Mitulescu, W. Skalli, D. Mitton, and J. A. De Guise.
   Three-dimensional surface rendering reconstruction of scoliotic vertebrae using a non stereo-corresponding
   points technique.
   European Spine Journal, 2002.
   Shinichiro Mori, Masanao Kobayashi, Motoki Kumagai, and Shinichi Minohara.
   Development of a gpu-based multithreaded software application to calculate digitally reconstructed radiographs
   for radiotherapy.
   Radiological Physics and Technology, 2009.
   Daniel C. Moura, Jorge G. Barbosa, João Manuel R. S. Tavares, and Ana M. Reis.
   Calibration of Bi-planar Radiography with a Rangefinder and a Small Calibration Object, pages 572–581.
   Springer Berlin / Heidelberg, 2008.
   Daniel C. Moura, Jonathan Boisvert, Jorge G. Barbosa, and João Manuel Tavares.
   Fast 3d reconstruction of the spine using user-defined splines and a statistical articulated model.
   In ISVC ’09: Proceedings of the 5th International Symposium on Advances in Visual Computing, pages
   586–595, Berlin, Heidelberg, 2009. Springer-Verlag.
   Daniel Russakoff, Torsten Rohlfing, Daniel Rueckert, Ramin Shahidi, Daniel Kim, Daniel Kima, Calvin R.
   Maurer, and Jr.
   Fast calculation of digitally reconstructed radiographs using light fields, 2003.
   F. P. Vidal, M. Garnier, N. Freud, J. M. Létang, and N. W. John.
   Simulation of x-ray attenuation on the gpu.
   In Proceeding of TCPG’09 - Theory and Practice of Computer Graphics, pages 25–32. Eurographics, June
   2009.
                         André dos Santos Cardoso            DRR Generation                                         11 / 11

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Generation of planar radiographs from 3D anatomical models using the GPU

  • 1. Generation of planar radiographs from 3D anatomical models using the GPU André dos Santos Cardoso Supervisor: Jorge M. G. Barbosa University of Porto Faculty of Engineering of University of Porto andre.cardoso@fe.up.pt, jbarbosa@fe.up.pt May 10, 2010 André dos Santos Cardoso DRR Generation 1 / 11
  • 2. Contents 1 Introduction Context Overview Project’s Objective 2 State of the Art 3 Detailed Objectives Technologies 4 Work Plan 5 Bibliography André dos Santos Cardoso DRR Generation 2 / 11
  • 3. Context Overview Digitally Reconstructed Radiographs (DRRs) Taking a radiography from 3D digital anatomical models – vertebrae models in this case Form of depth peeling, using ray-casting Key component in 2D/3D registration process André dos Santos Cardoso DRR Generation 3 / 11
  • 4. Context Overview DRRs are taken from vertebrae models built with 3D meshes DRR generation as mean to validate and/or correct the reconstructed 3D models Vertebrae Shape Recovery Using 2D/3D Non-Rigid Registration Important techniques for Scoliosis treatment and follow-ups Volume recovery using Biplanar Radiography Techniques Alternatives to MRIs and CTs André dos Santos Cardoso DRR Generation 4 / 11
  • 5. Project’s Objective Build Fast DRR Algorithms DRR calculation is a bottleneck 3D reconstruction usage in a daily basis requires high performances Take advantage of processing power of new GPUs Common workstations could do the job! André dos Santos Cardoso DRR Generation 5 / 11
  • 6. State of the Art Algorithms are variations of depth peeling using ray-casting, and attenuation law for bone material Few Applications of DRR to 3D Meshes (most work on CT data – voxels) Using OpenGL Shading Language (GLSL) Multi Pass Algorithm is available Single Pass Algorithm is considered the state of the art, but no applied implementation exists Compute Unified Device Architecture (CUDA) peeling examples exist (no DRR examples) André dos Santos Cardoso DRR Generation 6 / 11
  • 7. Detailed Objectives Enhance the existing solution Implement Single Pass Algorithm using GLSL Technology Implement Single Pass Algorithm using CUDA Technology Compare and evaluate attained solutions with existing approaches André dos Santos Cardoso DRR Generation 7 / 11
  • 8. Technologies C/C++ programming using OpenGL and CUDA Intended solution working both on Windows and *nix systems Visual Studio 2008 / Vim :) Possible packaging of solution as open-source library GLSL is part of the OpengGL standard provides mechanism to change graphics pipeline, using shaders CUDA is a Nvidia proprietary technology Nvidia’s CUDA SDK provides C/C++ extensions to execute paralell code directly on the GPU André dos Santos Cardoso DRR Generation 8 / 11
  • 9. Work Plan André dos Santos Cardoso DRR Generation 9 / 11
  • 10. Thank You for Listening! Ask Away! André dos Santos Cardoso DRR Generation 10 / 11
  • 11. Bibliography Cass Everitt. Interactive order-independent transparency. NVIDIA OpenGL Applications Engineering. 05/15/2001. Accessed in April 29, 2010. http://developer.nvidia.com/object/Interactive_Order_Transparency.html. Fang Liu, Meng-Cheng Huang, Xue-Hui Liu, and En-Hua Wu. Freepipe: a programmable parallel rendering architecture for efficient multi-fragment effects. In I3D ’10: Proceedings of the 2010 ACM SIGGRAPH symposium on Interactive 3D Graphics and Games, pages 75–82, New York, NY, USA, 2010. ACM. A. Mitulescu, W. Skalli, D. Mitton, and J. A. De Guise. Three-dimensional surface rendering reconstruction of scoliotic vertebrae using a non stereo-corresponding points technique. European Spine Journal, 2002. Shinichiro Mori, Masanao Kobayashi, Motoki Kumagai, and Shinichi Minohara. Development of a gpu-based multithreaded software application to calculate digitally reconstructed radiographs for radiotherapy. Radiological Physics and Technology, 2009. Daniel C. Moura, Jorge G. Barbosa, João Manuel R. S. Tavares, and Ana M. Reis. Calibration of Bi-planar Radiography with a Rangefinder and a Small Calibration Object, pages 572–581. Springer Berlin / Heidelberg, 2008. Daniel C. Moura, Jonathan Boisvert, Jorge G. Barbosa, and João Manuel Tavares. Fast 3d reconstruction of the spine using user-defined splines and a statistical articulated model. In ISVC ’09: Proceedings of the 5th International Symposium on Advances in Visual Computing, pages 586–595, Berlin, Heidelberg, 2009. Springer-Verlag. Daniel Russakoff, Torsten Rohlfing, Daniel Rueckert, Ramin Shahidi, Daniel Kim, Daniel Kima, Calvin R. Maurer, and Jr. Fast calculation of digitally reconstructed radiographs using light fields, 2003. F. P. Vidal, M. Garnier, N. Freud, J. M. Létang, and N. W. John. Simulation of x-ray attenuation on the gpu. In Proceeding of TCPG’09 - Theory and Practice of Computer Graphics, pages 25–32. Eurographics, June 2009. André dos Santos Cardoso DRR Generation 11 / 11