No reference quality evaluation of medical image fusion. Issue 4 (27th June 2018) - Tang, Lu; Tian, Chuangeng; Qian, Jiansheng; Li, Leida
Abstract: 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.