• DocumentCode
    723720
  • Title

    Medical images stabilization using sparse-induced similarity measure

  • Author

    Hariri, Ali ; Arabshahi, Soroush ; Ghafari, Aboozar ; Fatemizadeh, Emad

  • Author_Institution
    Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran, Iran
  • fYear
    2015
  • fDate
    11-12 March 2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Medical image stabilization has been widely used for clinical imaging modalities. Registration is a conspicuous stage for stabilizing dynamic medical images. Some of regular methods are sensitive to bias field distortion. Sparse-induced similarity measure (SISM) is a robust registering method against spatially-varying intensity distortions which is not evitable on clinical imaging instruments. This paper presents a method for registering medical images to average of captured images using SISM method to avoid spatially-varying intensity distortions like Bias field. Proposed method is compared with SSD and MI similarity measure based registrations. Results show enhancement in stabilizing medical dynamic images with SISM method.
  • Keywords
    image capture; image enhancement; image matching; image registration; medical image processing; MI similarity measure based registration; SISM method; SSD similarity measure based registration; bias field; clinical imaging instruments; clinical imaging modalities; dynamic medical image stabilization; image enhancement; medical image registration; robust registering method; sparse-induced similarity measure; spatially-varying intensity distortions; Biomedical imaging; Dictionaries; Distortion; Distortion measurement; Image analysis; Image registration; Transforms; Medical dynamic images; Sparse-induced similarity measurement; Spatially-varying intensity distortion; Stabilization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition and Image Analysis (IPRIA), 2015 2nd International Conference on
  • Conference_Location
    Rasht
  • Print_ISBN
    978-1-4799-8444-2
  • Type

    conf

  • DOI
    10.1109/PRIA.2015.7161624
  • Filename
    7161624