A Parallel Image Registration Algorithm Based on a Lattice Boltzmann Model

Yu Chen,Dongxiang Lu,Guy Courbebaisse

doi:10.3390/info11010001

Abstract

Image registration is a key pre-procedure for high level image processing. However, taking into consideration the complexity and accuracy of the algorithm, the image registration algorithm always has high time complexity. To speed up the registration algorithm, parallel computation is a relevant strategy. Parallelizing the algorithm by implementing Lattice Boltzmann method (LBM) seems a good candidate. In consequence, this paper proposes a novel parallel LBM based model (LB model) for image registration. The main idea of our method consists in simulating the convection diffusion equation through a LB model with an ad hoc collision term. By applying our method on computed tomography angiography images (CTA images), Magnet Resonance images (MR images), natural scene image and artificial images, our model proves to be faster than classical methods and achieves accurate registration. In the continuity of 2D image registration model, the LB model is extended to 3D volume registration providing excellent results in domain such as medical imaging. Our method can run on massively parallel architectures, ranging from embedded field programmable gate arrays (FPGAs) and digital signal processors (DSPs) up to graphics processing units (GPUs).

Highlights

Lattice Boltzmann (LB) method was first introduced as a powerful numerical tool for solving partial differential equations (PDE) in computational fluid dynamics (CFD) [1,2]
The basic idea of the LB model is the construction of simplified discrete dynamics for simulating the macroscopic model, which is described by partial differential equations (PDEs) using densities of particles moving on a regular lattice
The general lattice Boltzmann modeling consists in two steps: a translation step, during which particles move from node to node on a lattice, and a collision step, during which particles are redistributed at each node

Summary

Introduction

Lattice Boltzmann (LB) method was first introduced as a powerful numerical tool for solving partial differential equations (PDE) in computational fluid dynamics (CFD) [1,2]. The biggest difference between the LB method and the traditional numerical methods is due to the fact that the LB method is based on the microscopic description of physical systems. By simulating the microscopic behavior of physical systems, the macroscopic equation of the LB method can match certain PDEs. The idea of the LB method is to transpose discrete dynamics for simulating the macroscopic model described by a PDE, using densities of particles colliding and streaming on a regular lattice [3]. Adapted to parallel calculation, the LB method is a good candidate for massive parallel computation

Methods

Results

Discussion

Conclusion