• DocumentCode
    245868
  • Title

    Detail-Enhanced Multimodal Medical Image Fusion

  • Author

    Guocheng Yang ; Leiting Chen ; Hang Qiu

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2014
  • fDate
    19-21 Dec. 2014
  • Firstpage
    1611
  • Lastpage
    1615
  • Abstract
    Many traditional medical image fusion methods cannot well preserve details of source images in the fused image. Aiming at handling this issue, a novel medical image fusion scheme based on gain control is developed by nonsubsampled contour let transform (NSCT). To enhance image details, the proposed method applies power law transformation to tune coefficients of each decomposed sub band, and adjusts the strength of the sub band signals by smooth gain control. Finally, the fused image with more details is constructed by the inverse NSCT. Experimental results demonstrate that our method can produce better fusion performance than some existing methods by the comparison of visual perception and objective quality assessment.
  • Keywords
    image fusion; medical image processing; transforms; NSCT; detail-enhanced multimodal medical image fusion; gain control; nonsubsampled contourlet transform; objective quality assessment; source images; sub band signals; Discrete wavelet transforms; Gain control; Image fusion; Magnetic resonance imaging; Medical diagnostic imaging; Principal component analysis; NSCT; gain control; medical image fusion; quality assessment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4799-7980-6
  • Type

    conf

  • DOI
    10.1109/CSE.2014.297
  • Filename
    7023808