基于模因规划算法的区域生长阈值自适应

A. Ayman, Emad Hamdy, Zanaty Elnomery
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引用次数: 1

摘要

提出了一种体积磁共振成像(MRI)脑图像分割的新方法。我们提出了一种新的分割技术,该技术将一种称为模因规划(MP)算法的进化算法与区域生长(RG)技术相结合。MP算法生成新的阈值函数,RG利用这些阈值对MRI图像进行有效分割。通过一组具有不同噪声和射频电平的医学图像对所提出的分割技术进行了测试。实验结果表明,该方法能获得更准确、更有前景的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptation of Region Growing thresholds using Memetic Programming algorithm
This paper presents a new strategy for the segmentation of brain images from the volumetric Magnetic Resonance Imaging (MRI). We propose a new segmentation technique that hybridize an evolutionary algorithm, called the Memetic Programming (MP) algorithm, with the Region Growing (RG) technique. The MP algorithm generates new threshold functions and then the RG uses these thresholds to perform an efficient segmentation of MRI images. The proposed segmentation technique are tested through a set of medical images with different noise and Radio Frequency (RF) levels. The experimental results show that the proposed technique produces more accurate and promising results.
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