Generation of planar radiographs from 3D anatomical models using the GPU
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
May 10, 2010
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2 State of the Art
3 Detailed Objectives
4 Work Plan
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Digitally Reconstructed Radiographs
Taking a radiography from 3D digital
anatomical models – vertebrae models
in this case
Form of depth peeling, using
Key component in 2D/3D registration
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DRRs are taken from vertebrae models built with 3D
DRR generation as mean to validate and/or correct the
reconstructed 3D models
Vertebrae Shape Recovery Using 2D/3D Non-Rigid
Important techniques for Scoliosis treatment and follow-ups
Volume recovery using Biplanar Radiography Techniques
Alternatives to MRIs and CTs
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Build Fast DRR Algorithms
DRR calculation is a bottleneck
3D reconstruction usage in a
daily basis requires high
Take advantage of processing
power of new GPUs
Common workstations could do
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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)
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Enhance the existing solution
Implement Single Pass Algorithm using
Implement Single Pass Algorithm using
Compare and evaluate attained
solutions with existing approaches
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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
CUDA is a Nvidia proprietary technology
Nvidia’s CUDA SDK provides C/C++ extensions to execute
paralell code directly on the GPU
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Thank You for Listening!
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