Metaheuristics for Medical Image Registration

  • Andrea ValsecchiEmail author
  • Enrique Bermejo
  • Sergio Damas
  • Oscar Cordón
Reference work entry


In the last few decades, image registration (IR) has been a very active research area in computer vision. Applications of IR cover a broad range of real-world problems, including remote sensing, medical imaging, artificial vision, and computer-aided design. In particular, medical IR is a mature research field with theoretical support and two decades of practical experience. Formulated as either a continuous or combinatorial optimization problem, medical IR has been traditionally tackled by iterative numerical optimization methods, which are likely to get stuck in local optima and deliver suboptimal solutions. Recently, a large number of medical IR methods based on different metaheuristics, mostly belonging to evolutionary computation, have been proposed. In this chapter, we review the most recognized of these algorithms and develop an experimental comparison over real-world IR scenarios.


Medical imaging Image registration Image segmentation 



This work is supported by the Spanish “Ministerio de Economía y Competitividad” under the NEWSOCO project (ref. TIN2015-53067661) and the Andalusian Department of Innovación, Ciencia y Empresa under project TIC2011-7745, both including European Regional Development Funds (ERDF).


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Andrea Valsecchi
    • 1
    Email author
  • Enrique Bermejo
    • 1
  • Sergio Damas
    • 2
  • Oscar Cordón
    • 1
  1. 1.Department of Computer Science and Artificial IntelligenceUnviersity of GranadaGranadaSpain
  2. 2.Department Software EngineeringUniversity of GranadaGranadaSpain

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