差分进化算法在脑肿瘤图像融合识别中的应用

Pub Date : 2020-03-23 DOI:10.17993/3ctecno.2020.specialissue4.301-311

P. Sivakumar, S. Velmurugan, Jenyfal Sampson

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引用次数: 8

摘要

自动化机械化治疗疾病是一种可靠且突出的方法。大脑中的疾病可以通过核磁共振成像（MRI）来检测。在这种情况下，图像融合是一种通过合并来自2个或多个图像的相关数据来创建图像的方法。所得到的图像将比单独的输入图像更有用，以保持每个图像的重要特征。多图像融合是图像处理技术中的一种重要方法。在本研究中，对MRI和计算机断层扫描（CT）图像进行了基于差分进化（DE）算法的图像融合。已经进行了仿真工作来评估DE在图像融合上的不同质量测量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Implementation of differential evolution algorithm to perform image fusion for identifying brain tumor

Automated mechanization for curing a disease is a reliable and protuberant method. A disease in brain can be detected by Magnetic Resonance Imaging (MRI). In this context, image fusion is a method for creating an image by merging pertinent data from 2 or more images. The resultant image will be highly useful than the individual input images to retentive the vital characteristics of every image. Multiple image fusion is a significant method employed in image processing techniques. In this study, differential evolution (DE) algorithm-based image fusion has been performed with MRI and computed tomography (CT) images. The simulation works have been carried out to evaluate the different quality measurements of DE on image fusion.

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