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Real-time synchronous hardware architecture for MRI images segmentation based on PSO

机译:基于PSO的MRI图像分段实时同步硬件架构

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Particle Swarm Optimization (PSO) is a metaheuristic algorithm based optimization technique for continuous search problem. It is among the most used algorithms in various areas of application. Its popularity has exceeded the deferred-time problems to the real-time problems that require the use of embedded architectures. Many real-time applications include mobile robots and medical image processing has been widely developed and improved using PSO by many researchers. We have succeeded the implementation of the real-time segmentation of MRI medical images based on PSO algorithm in previous work. In this paper, we try to extend the work by adding a control unit that controls each task of the various blocks of the architecture. Therefore, the new obtained synchronous architecture of MRI images segmentation based PSO allows to save execution time and thus narrow the search procedure of the optimal threshold. The performance of the proposed synchronous hardware architecture is evaluated and validated using a set of MRI medical images.
机译:粒子群优化(PSO)是一种基于常规搜索问题的基于成群质算法的优化技术。它是各种应用领域中最常用的算法之一。它的受欢迎程度超过了需要使用嵌入式架构的实时问题的延期时间问题。许多实时应用包括移动机器人和医学图像处理已被许多研究人员使用PSO广泛开发和改进。我们成功地实施了基于PSO算法的MRI医学图像的实时分割。在本文中,我们尝试通过添加控制架构的各个块的每个任务的控制单元来扩展工作。因此,基于MRI图像分割的PSO的新获得的同步架构允许节省执行时间,从而缩小最佳阈值的搜索过程。使用一组MRI医学图像进行评估和验证所提出的同步硬件架构的性能。

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