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No reference quality evaluation of medical image fusion

机译:没有医学影像融合的参考质量评估

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摘要

Medical image fusion (MIF) attracts much attention in clinical use. Many MIF algorithms have been proposed over the past decade. Existing MIF algorithms create different fused image, however, current quality evaluation method is not designed for MIF images. So, we present a no reference quality evaluation of medical image fusion. Firstly, a MIF image database (MIFID) is built, and radiologist ratings are selected to conduct subjective test. Then an objective quality evaluation metric of medical image fusion is proposed via the phase congruency and standard deviation. Image salient features and image information are very important for visual quality of fused image. Based on this consideration, we combine the two existing quality evaluation metrics to assess MIF images. Finally, five comparative study experiments are implemented based on the MIFID. Experimental results reveal that the proposed quality evaluation metric is superior to the existing state-of-the-art metrics, which is more applicable to evaluate MIF images.
机译:医学图像融合(MIF)在临床上引起了很多关注。在过去的十年中,已经提出了许多MIF算法。现有的MIF算法会创建不同的融合图像,但是,当前的质量评估方法并未设计用于MIF图像。因此,我们提出医学图像融合的无参考质量评估。首先,建立一个MIF图像数据库(MIFID),并选择放射线医师的评分进行主观测试。然后通过相位一致性和标准差提出了医学图像融合的客观质量评价指标。图像显着特征和图像信息对于融合图像的视觉质量非常重要。基于此考虑,我们结合了两个现有的质量评估指标来评估MIF图像。最后,基于MIFID进行了五个比较研究实验。实验结果表明,提出的质量评估指标优于现有的最新指标,它更适用于评估MIF图像。

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