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Handbook of Heuristics pp 1079–1101Cite as

Metaheuristics for Medical Image Registration

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Abstract

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.

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Acknowledgements

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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Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, Unviersity of Granada, Granada, Spain

    Andrea Valsecchi, Enrique Bermejo & Oscar Cordón

  2. Department Software Engineering, University of Granada, Granada, Spain

    Sergio Damas

Authors
  1. Andrea Valsecchi
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  2. Enrique Bermejo
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  3. Sergio Damas
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  4. Oscar Cordón
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Corresponding author

Correspondence to Andrea Valsecchi .

Editor information

Editors and Affiliations

  1. Statistics and Operations Research Department, University of Valencia, Valencia, Spain

    Rafael Martí

  2. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  3. Amazon.com, Inc. and University of Washington, Seattle, Washington, USA

    Mauricio G. C. Resende

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Valsecchi, A., Bermejo, E., Damas, S., Cordón, O. (2018). Metaheuristics for Medical Image Registration. In: Martí, R., Pardalos, P., Resende, M. (eds) Handbook of Heuristics. Springer, Cham. https://doi.org/10.1007/978-3-319-07124-4_56

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