Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (15): 208-214.DOI: 10.3778/j.issn.1002-8331.1906-0429

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Medical Image Fusion Algorithm Based on Laplacian Pyramid and CNN

WU Fan, GAO Yuan, QIN Pinle, WANG Lifang   

  1. School of Big Data, North University of China, Taiyuan 030051, China
  • Online:2020-08-01 Published:2020-07-30



  1. 中北大学 大数据学院,太原 030051


Medical image fusion technology plays an increasingly important role in clinical application because it contains multimodal image information. The fusion effect of medical image is more in line with human visual perception, reducing the influence of prior knowledge on the fusion effect and enhancing the detail expression. In this paper, a medical image fusion method based on Laplacian pyramid and convolutional neural network is proposed. Aiming at the problem of image artifacts, the regional Laplacian pyramid is adopted to improve the convolutional neural network in order to save more details and make parameters adaptive. The source images are input into the Laplacian pyramid for decomposition, and the improved convolutional neural network is used to generate the optimal weight graph to guide the fusion process. Finally, the fusion images are generated through the inverse process. Experimental results show that the method achieves good fusion effect on subjective vision and objective evaluation indexes.

Key words: medical image fusion, Laplacian pyramid, Convolutional Neural Network(CNN)



关键词: 医学图像融合, 拉普拉斯金字塔, 卷积神经网络