Real-time intensity-based rigid 2d-3d medical image registration using RapidMind Multi-core Development Platform.
In this paper, we present an efficient intensity-based rigid 2D-3D image registration method. We implement the algorithm using the RapidMind Multi-core Development Platform(1) to exploit the highly parallel multi-core architecture of graphics processing units (GPUs). We use a ray casting algorithm to generate the digitally reconstructed radiographs (DRRs) on GPUs and efficiently reduce the complexity of DRR construction. The registration optimization problem is solved by the Gauss-Newton method. To fully exploit the multi-core parallelism, we implement almost the entire registration process in parallel by RapidMind. We also discuss the RapidMind implementation of the major computation steps. Numerical results are presented to demonstrate the efficiency of our method.
Xu
Lin
L
David R. Cheriton School of Computer Science, University of Waterloo, Ontario, Canada. jwlwan@uwaterloo.ca
Wan
Justin W L
JW
D000465:Algorithms; D001185:Artificial Intelligence; D003199:Computer Systems; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity