• DocumentCode
    3283136
  • Title

    Research on a novel non-rigid registration for medical image based on SURF and APSO

  • Author

    Wang, Aiping ; Zhe Wang ; Dan Lv ; Zhizhen Fang

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • Volume
    6
  • fYear
    2010
  • fDate
    16-18 Oct. 2010
  • Firstpage
    2628
  • Lastpage
    2633
  • Abstract
    Registration of medical image has become an important research subject. For the large image distortion of some special places, the non-rigid registration is more accurate and necessary to afford important reference value for clinical care compared with the rigid registration. In order to realize robust and efficient registration, a novel non-rigid registration method for medical image based on Speeded Up Robust Features (SURF) and Adapted Particle Swarm Optimization (APSO) algorithm was proposed in the paper. In the process of registration, SURF descriptor is used to extract scale and rotation invariant features with little calculating time, furthermore APSO algorithm can avoid falling into local optimum with fast convergence speed during searching for optimal parameters. The experimental results show that the method with SURF and APSO is faster and more robust than traditional registration algorithm.
  • Keywords
    feature extraction; health care; image registration; medical image processing; particle swarm optimisation; search problems; APSO; SURF; adapted particle swarm optimization; clinical care; image distortion; medical image Registration; novel nonrigid registration; rotation invariant feature extraction; speeded up robust feature; Biomedical imaging; Convergence; Feature extraction; Image registration; Optimization; Positron emission tomography; Robustness; APSO; SURF; affine transformation; non-rigid image registration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2010 3rd International Congress on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4244-6513-2
  • Type

    conf

  • DOI
    10.1109/CISP.2010.5648148
  • Filename
    5648148