Perceptual quality assessment for multimodal medical image fusion

作者：

Highlights：

• In this paper, we construct a multimodal medical image fusion (MMIF) image database.

• We proposed a perceptual MMIF quality evaluation metric. The effectiveness of the designed metric is verified on the (MMIF) image database.

• Experimental results show that the proposed metric achieves superiority over existing image fusion quality evaluation algorithms in terms of consistent alignment with subjective ratings of MMIF images.

摘要

•In this paper, we construct a multimodal medical image fusion (MMIF) image database.•We proposed a perceptual MMIF quality evaluation metric. The effectiveness of the designed metric is verified on the (MMIF) image database.•Experimental results show that the proposed metric achieves superiority over existing image fusion quality evaluation algorithms in terms of consistent alignment with subjective ratings of MMIF images.

论文关键词：Subjective and objective quality assessment,Multimodal medical image fusion,MMIF image database,Pulse coupled neural network,Non-subsampled contourlet transform

论文评审过程：Received 23 April 2019, Revised 23 December 2019, Accepted 7 April 2020, Available online 20 April 2020, Version of Record 22 April 2020.

论文官网地址：https://doi.org/10.1016/j.image.2020.115852