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Segmentation of tumor in digital mammograms using wavelet transform modulus maxima on a low cost parallel computing system

机译:在低成本并行计算系统上使用小波变换模极大值在数字乳腺X线照片中分割肿瘤

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摘要

Parallel Computing System (PCS) is currently used widely in many applications of complex problems involving high computations. This is because it has the capability to process computations efficiently using a parallel scheme. ARS cluster is a low-cost PCS developed to implement processing of full-field digital mammograms. In this system eight processors are used to communicate via the Ethernet network using LINUX which is Fedora 7 as the operating system and Matlab Distributed Computing Server (MDCS) as a platform to process the digital mammograms. In this paper the Wavelet Transforms Modulus Maxima (WTMM) method is used to detect the edge of tumor in digital mammogram implemented on the ARS cluster. The study involved 80 digitized mammographic images obtained from the Malaysian National Cancer Center (NCC). The performance of the PCS in detecting the edge of tumors in digital mammograms using WTMM on the ARS cluster is reported. The experimental results showed that the speedup of the PCS improves when the number of processors is increased. © 2011 Springer-Verlag.
机译:并行计算系统(PCS)当前广泛用于涉及高计算量的复杂问题的许多应用中。这是因为它具有使用并行方案高效处理计算的能力。 ARS集群是开发用于实现全场数字乳房X线照片处理的低成本PCS。在该系统中,使用LINUX(以Fedora 7为操作系统,Matlab分布式计算服务器(MDCS)作为平台)来处理8个处理器,以通过以太网网络进行以太网通信。本文采用小波变换模量极大值(WTMM)方法在ARS集群上实现的数字乳房X光照片中检测肿瘤的边缘。该研究涉及从马来西亚国家癌症中心(NCC)获得的80幅数字化乳腺X线照片。报告了PCS在ARS簇上使用WTMM在数字乳房X线照片中检测肿瘤边缘的性能。实验结果表明,随着处理器数量的增加,PCS的速度提高。 ©2011年Springer-Verlag。

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