Multimodal Medical Image Fusion Based on Two-Scale Decomposer and Detail Preservation Model

이중스케일분해기와 미세정보 보존모델에 기반한 다중 모드 의료영상 융합연구

The purpose of multimodal medical image fusion (MMIF) is to integrate images of different modes with different details into a result image with rich information, which is convenient for doctors to accurately diagnose and treat the diseased tissues of patients. Encouraged by this purpose, this paper proposes a novel method based on a two-scale decomposer and detail preservation model. The first step is to use the two-scale decomposer to decompose the source image into the energy layers and structure layers, which have the characteristic of detail preservation. And then, structure tensor operator and max-abs are combined to fuse the structure layers. The detail preservation model is proposed for the fusion of the energy layers, which greatly improves the image performance. The fused image is achieved by summing up the two fused sub-images obtained by the above fusion rules. Experiments demonstrate that the proposed method has superior performance compared with the state-of-the-art fusion methods.