Abstract
Coronary artery (CA) disease is one of the major cardiovascular diseases that has been proved to be the leading cause of human death in world. In this paper, a 3D image segmentation algorithm based on Lattice Boltzmann (LB) is proposed for 3D CA segmentation. After investigating the behavior of Boundary Treatment schemes, a non-equilibrium extrapolation scheme is applied to keep the stability of the computation, and reduce the frequency of the re-initialization. The denoising and clipping method are also proposed for the segmentation refining. The segmentation result shows our LB model for 3D CAD segmentation is effective. More importantly, the LB model has natural parallelism. Our model can run on massively parallel architectures, ranging from inexpensive embedded FPGAs and DSPs up to GPUs.
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