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Parallel c-means algorithm for image segmentation on a reconfigurable mesh computer

机译:可重构网格计算机上用于图像分割的并行c均值算法

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摘要

In this paper, we propose a parallel algorithm for data classification, and its application for Magnetic Resonance Images (MRI) segmentation. The studied classification method is the well-known c-means method. The use of the parallel architecture in the classification domain is introduced in order to improve the complexities of the corresponding algorithms, so that they will be considered as a pre-processing procedure. The proposed algorithm is assigned to be implemented on a parallel machine, which is the reconfigurable mesh computer (RMC). The image of size (m x n) to be processed must be stored on the RMC of the same size, one pixel per processing element (PE).
机译:在本文中,我们提出了一种用于数据分类的并行算法,并将其应用于磁共振图像(MRI)分割。研究的分类方法是众所周知的c-means方法。为了提高相应算法的复杂性,引入了在分类域中使用并行体系结构的方法,以便将它们视为预处理过程。拟议的算法被分配为在并行机器上实现,该机器是可重构网格计算机(RMC)。必须将要处理的大小(m x n)的图像存储在相同大小的RMC上,每个处理元素(PE)一个像素。

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