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Improving the accuracy of 2D-3D registration of femur bone for bone fracture reduction robot using particle swarm optimization

A. M. Abdul Zaman, Seong Young Ko

发表年份
2018
引用次数
5

摘要

Population-based optimization algorithms have proved themselves very effective and efficient way for solving some complex problems, particularly for problems of non-linear and non-convex nature. 2D-3D registration is one such problem where inherent non-linearity and high-dimensionality along with non-convex optimization nature makes it very difficult to achieve satisfying accuracy especially when starting point for optimization is not ideal. Because of the underlying structure of population-based optimization algorithms, especially particle swarm optimization (PSO), 2D-3D registration with PSO is expected to yield better accuracy compared to conventional gradient-based optimization algorithms. Another considerable factor is that gradient approximation error makes non-gradient methods more favorable for the case of 2D-3D registration over gradient-based methods. Our experiment on 2D-3D registration using virtual X-ray shows that PSO has better accuracy and convergence rate than gradient based approaches like Stochastic Gradient Descent (SGD), Momentum Stochastic Gradient Descent (MSGD) and Nesterov Accelerated Gradient (NAG).

关键词

Stochastic gradient descentParticle swarm optimizationGradient descentProximal Gradient MethodsMathematical optimizationComputer scienceGradient methodOptimization problemRate of convergenceMulti-swarm optimization

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