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Design of Static Metaheuristics for Medical Image Analysis

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Metaheuristics for Medicine and Biology

Part of the book series: Studies in Computational Intelligence ((SCI,volume 704))

Abstract

Medical images, such as Computed Axial Tomography (CAT), Magnetic Resonance Imaging (MRI), Ultrasound, and X-Ray, in standard DICOM (Digital Imaging and Communications in Medicine) formats are often stored in Picture Archiving and Communication Systems (PACS) and linked with other clinical information in clinical management systems.

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Acknowledgements

The author would like to thank, Agnes Masson-Sibut, Salma Hajjem, Hamouche Oulhadj, Amitava Chaterjee and Patrick Siarry for their collaboration.

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Authors and Affiliations

  1. Laboratoire LISSI, Université Paris Est, 122 Rue P. Armangot, 94400, Vitry-sur-Seine, France

    Amir Nakib

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  1. Amir Nakib
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Correspondence to Amir Nakib .

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Editors and Affiliations

  1. Signaux et Systèmes Intelligents, Université Paris Est Créteil, Laboratoire Images, Créteil, France

    Amir Nakib

  2. INRIA Lille Nord Europe Parc Scientifique de la Haute Borne, Laboratoire d'Informatique Fondamentale de Lille (UMR CNRS 8022), Villeneuve d'Ascq, France

    El-Ghazali Talbi

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Nakib, A. (2017). Design of Static Metaheuristics for Medical Image Analysis. In: Nakib, A., Talbi, EG. (eds) Metaheuristics for Medicine and Biology. Studies in Computational Intelligence, vol 704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54428-0_1

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  • DOI: https://doi.org/10.1007/978-3-662-54428-0_1

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  • Print ISBN: 978-3-662-54426-6

  • Online ISBN: 978-3-662-54428-0

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