A Hybrid Fusion Model for Brain Tumor Images of MRI and CT

V. Rani, S. Lalithakumari
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Abstract

Multimodal medical image fusion helps to acquire more information about both the functional and structural informations. More over storage problems can also be addressed properly when the fusion process is adopted. A hybrid image fusion is being sought for an optimum algorithm for a better quality image. This proposed work describes about the multimodal image fusion framework based on empirical mode decomposition of images and fusion by discrete wavelet transform method. The obtained fused image by the proposed method consists of all the functional information and also the spatial characteristics of original image. No distortion is also present in the fused image. In this proposed work Magnetic Resonance Imaging (MRI), and Computerized Tomography (CT) images of brain are used for fusion. The fusion results obtained by this method are observed and quantitatively analyzed. The hybrid fusion response of this approach depicts the dominance of the acquired results.
脑肿瘤MRI和CT图像的混合融合模型
多模态医学图像融合有助于获取更多的功能信息和结构信息。当采用融合工艺时,也可以适当地解决更多的过度存储问题。在混合图像融合中寻求一种最优算法以获得更好的图像质量。提出了一种基于图像经验模态分解和离散小波变换融合的多模态图像融合框架。该方法得到的融合图像既包含了原始图像的所有功能信息,又包含了原始图像的空间特征。融合后的图像也没有失真。在这项工作中,磁共振成像(MRI)和计算机断层扫描(CT)图像的脑融合。对该方法得到的融合结果进行了观察和定量分析。这种方法的混合融合响应描述了所获得结果的优势。
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