不同图像融合技术在生物医学图像中的应用比较研究

C. Ghandour, W. El-shafai, S. El-Rabaie
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引用次数: 2

摘要

医学图像融合是各种图像处理应用的重要领域。近年来,图像融合算法的扩展得到了更多的努力和进展,但缺乏可对最先进的作品进行扩展的基准和代码库。在本研究中,针对不同的医学图像实现了不同的图像融合算法。介绍了一种包含多种评价指标和融合算法代码库的医学图像融合基准测试系统。此外,在基准内,还进行了包容性实验来实现这一性能,通过解决定量和定性结果来区分有效的图像融合算法,并对该领域的状态和未来可能性进行了一些观察。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative Study between Different Image Fusion Techniques Applied on Biomedical Images
The significant area in varied image processing applications is medical image fusion. In recent years, more efforts, advancement has been made on expanding image fusion algorithms when there is a scarcity of benchmark and code library that can scale the state-of-the-art works. In this research, different image fusion algorithms are implemented on various medical images. A medical image fusion benchmark (MFB) that includes numerous evaluation metrics and fusion algorithms code library is exhibited. Furthermore, within the benchmark, inclusive experiments are also carried out to realize this performance, effective algorithms for powerful image fusion are distinguished by resolving quantitative and qualitative outcomes, and some observances on the states and future likelihoods of this field are granted.
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