基于区域的图像融合检测Ewing肉瘤

T. Zaveri, M. Zaveri
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引用次数: 12

摘要

在医学图像处理中,不同来源的图像提供了互补的信息,因此不同来源图像的融合将为患者的诊断提供更多的细节。提出了一种基于自动区域的图像融合算法,并将其应用于人脑核磁共振图像的配准。本文的目的是检测准确诊断脑肿瘤所需的所有信息,即尤因肉瘤,同时在单个MR图像中不可用。将所提出的基于区域的图像融合方法应用于两类磁共振序列图像,提取有用信息,并与不同的基于像素的融合算法进行比较,使用标准质量评价参数对融合方案的性能进行评价。通过对质量评价参数的分析,发现该方案比基于像素的融合方案具有更好的效果。由此产生的融合图像由放射科医生评估和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Region Based Image Fusion for Detection of Ewing Sarcoma
In the medical image processing different sources of images are providing complementary information so fusion of different source images will give more details for diagnosis of patients. In this paper an automatic region based image fusion algorithm is proposed which is applied on the registered Magnetic Resonance (MR) image of human brain. The aim of this paper is to detect all the information required for accurate diagnosis of a brain tumor namely, Ewing sarcoma which is simultaneously not available in individual MR images. The proposed region based image fusion method is applied on two types of MR sequence images to extract useful information which is than compared with different pixel based algorithm and the performance of these fusion schemes are evaluated using standard quality assessment parameters. From the analysis of quality assessment parameters we found that our scheme provides better result compared to pixel based fusion scheme. The resultant fused image is assessed and validated by radiologist.
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