• DocumentCode
    631765
  • Title

    Genetic algorithms for Voxel-based medical image registration

  • Author

    Valsecchi, Andrea ; Damas, Sergio ; Santamaria, J. ; Marrakchi-Kacem, Linda

  • Author_Institution
    Eur. Centre for Soft Comput., Mieres, Spain
  • fYear
    2013
  • fDate
    16-19 April 2013
  • Firstpage
    22
  • Lastpage
    29
  • Abstract
    Image registration (IR) - the task of aligning different images having a common content - is a fundamental problem in computer vision. In particular, IR is one of the key steps in medical imaging, with applications ranging from computer assisted diagnosis to computer aided therapy and surgery. As IR can be formulated as an optimization problem, a large family of metaheuristics methods can be used to improve the results obtained by classic gradient-based, continuous optimization techniques. In this work, we extend our previous intensity-based image registration (IR) technique based on a real-coded genetic algorithm with a more appropriate design. The performance evaluation of an heterogeneous group of state-of-the-art IR techniques is also extended to two experimental studies on both synthetic and real-word medical IR problems. The results prove the accuracy and applicability of our new method.
  • Keywords
    biomedical MRI; brain; computer vision; genetic algorithms; image registration; medical image processing; computer aided surgery; computer aided therapy; computer assisted diagnosis; computer vision; continuous optimization technique; genetic algorithm; gradient-based technique; image alignment; intensity-based image registration technique; metaheuristics method; voxel-based medical image registration; Algorithm design and analysis; Biomedical imaging; Genetic algorithms; Image resolution; Magnetic resonance imaging; Measurement; Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Medical Imaging (CIMI), 2013 IEEE Fourth International Workshop on
  • Conference_Location
    Singapore
  • ISSN
    2326-991X
  • Print_ISBN
    978-1-4673-5919-1
  • Type

    conf

  • DOI
    10.1109/CIMI.2013.6583853
  • Filename
    6583853