• DocumentCode
    3692213
  • Title

    Discover layered structure in ultrasound images with a joint sparse representation model

  • Author

    Junbo Duan; Hui Zhong; Bowen Jing; Siyuan Zhang; Mingxi Wan

  • Author_Institution
    The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering,School of Life Science and Technology, Xi´an Jiaotong University, Shaanxi, China
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Deconvolution can improve the resolution of ultrasound system since the effect of point spread function can be removed. Traditional methods carry out the deconvolution line by line, so the neighborhood information are unused. A joint sparse model is proposed in this work to discover layered structure in ultrasound images. The model joints the axial deconvolution with a sparse lateral constraint. The model was tested on simulation and real data, and results support the enhanced performance in terms of resolution.
  • Keywords
    "Deconvolution","Radio frequency","Convolution","Sparse matrices","Yttrium","Joints","Data models"
  • Publisher
    ieee
  • Conference_Titel
    Ultrasonics Symposium (IUS), 2015 IEEE International
  • Type

    conf

  • DOI
    10.1109/ULTSYM.2015.0323
  • Filename
    7329202
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3692213