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

机译:基于PSO的MRI图像实时同步硬件分割。

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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)是一种基于元启发式算法的连续搜索问题优化技术。它是各个应用领域中使用最广泛的算法之一。它的流行已经超越了延迟问题,成为了需要使用嵌入式体系结构的实时问题。许多实时应用程序包括移动机器人,许多研究人员使用PSO广泛开发和改进了医学图像处理。在先前的工作中,我们已经成功地实现了基于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该体系结构各个模块的每个任务的控制单元来扩展工作。因此,新获得的基于MRI图像分割的PSO同步架构可以节省执行时间,从而缩小了最佳阈值的搜索过程。使用一组MRI医学图像评估和验证了所提出的同步硬件体系结构的性能。

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