Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation - Liu, Shuaiqi; Wang, Mingwang; Yin, Lu; Sun, Xiuming; Zhang, Yu-Dong; Zhao, Jie (Frontiers in Computational Neuroscience, 2022)
Medical image fusion has an indispensable value in medicine field. Taking advantages of structure-preserving filter and deep learning, a structure preservation based two-scale multimodal medical image fusion algorithm is proposed. First, we use a two-scale decomposition method to decompose source images into base layer components and detail layer components. Second, we adopt a fusion method based on the iterative joint bilateral filter to fuse base layer components. Third, convolutional neural network and local similarity of images are used to fuse the components of detail layer. At the last, the final fused result is got by using two-scale image reconstruction. The contrast experiments display that our algorithm has better fusion results than the state-of-the-art medical image fusion algorithms.