Research on the Application of Medical Image Fusion Technology in Tumor Radiotherapy

Due to the lack of effective information in conventional medical images, referring to conventional medical images will affect the judgment of tumor condition, resulting in low clinical effect of tumor radiotherapy, so medical image fusion technology is proposed and applied to tumor radiotherapy. In this paper, the attention module is designed to adapt to the output of different scale feature maps, and the expression ability of key channel features is enhanced, which makes the important details of the image more prominent, and effectively solves the edge blurring phenomenon between different organizations. Finally, the cross-entropy loss combined with the center loss is used to calculate, so that the distribution of each class sample feature in the sample space is more optimized, and the fusion accuracy of the model is further improved. In the fused image, the edges of different tissues are clear and the details are rich. Experiments show that compared with the current advanced medical image fusion methods, the fusion effect of the proposed method is superior to that of the comparison methods in terms of subjective visual effect or objective evaluation index.