• DocumentCode
    681347
  • Title

    Sequence slices enhancement of peripheral nerve based on surfacelet transform

  • Author

    Feng Zhou ; Xiuli Ma ; Xiaojun Zhou ; Xia Chen

  • Author_Institution
    Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China
  • fYear
    2013
  • fDate
    19-20 Aug. 2013
  • Firstpage
    449
  • Lastpage
    452
  • Abstract
    Enhancement of nerve sequence slice images is a key step of three-dimensional reconstruction of peripheral nerve. This paper presents a truly multi-scale, multi-directional decomposition method called surfacelet transform for sequence slice images for the reason that low-contrast enhancement effect of nerve slice images is not obvious, the method takes nerve sequence slices as a three-dimensional space-time signal, on the basis of a single picture processing in the traditional transform domain processing, making an improvement, applied to nerves sequence slice CT image enhancement. Experimental data show that this method compared to other methods, can preserve the neurological details of CT images better, achieve high signal to noise ratio and better visual effects.
  • Keywords
    image enhancement; image reconstruction; image sequences; medical image processing; neurophysiology; transforms; CT image enhancement; low-contrast enhancement effect; multidirectional decomposition; multiscale decomposition; nerve sequence slice images; neurological details; peripheral nerve; sequence slices enhancement; single picture processing; surfacelet transform; three-dimensional reconstruction; three-dimensional space-time signal; transform domain processing; visual effects; Image Enhancement; Multi-directional; Multi-scale; Slice Sequence; Surfacelet;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Smart and Sustainable City 2013 (ICSSC 2013), IET International Conference on
  • Conference_Location
    Shanghai
  • Electronic_ISBN
    978-1-84919-707-6
  • Type

    conf

  • DOI
    10.1049/cp.2013.2019
  • Filename
    6737868