• The School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China;
Export PDF Favorites Scan Get Citation

Image fusion currently plays an important role in the diagnosis of prostate cancer (PCa). Selecting and developing a good image fusion algorithm is the core task of achieving image fusion, which determines whether the fusion image obtained is of good quality and can meet the actual needs of clinical application. In recent years, it has become one of the research hotspots of medical image fusion. In order to make a comprehensive study on the methods of medical image fusion, this paper reviewed the relevant literature published at home and abroad in recent years. Image fusion technologies were classified, and image fusion algorithms were divided into traditional fusion algorithms and deep learning (DL) fusion algorithms. The principles and workflow of some algorithms were analyzed and compared, their advantages and disadvantages were summarized, and relevant medical image data sets were introduced. Finally, the future development trend of medical image fusion algorithm was prospected, and the development direction of medical image fusion technology for the diagnosis of prostate cancer and other major diseases was pointed out.

Citation: LUO Wenbin, WANG Pei, ZHANG Yiwei, SHI Gengqiang. Advances in the diagnosis of prostate cancer based on image fusion. Journal of Biomedical Engineering, 2024, 41(5): 1078-1084. doi: 10.7507/1001-5515.202403054 Copy

  • Previous Article

    Research progress of breast pathology image diagnosis based on deep learning
  • Next Article

    Small-scale cross-layer fusion network for classification of diabetic retinopathy