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Metaheuristics for Medicine and Biology

  • Book
  • © 2017

Overview

Editors:
  1. Amir Nakib

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

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  2. El-Ghazali Talbi

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

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    You can also search for this editor in PubMed   Google Scholar

  • Includes recent research on metaheuristics for biomedical engineering
  • Explores both theoretical and applications aspects
  • Written by leading experts in the field
  • Includes supplementary material: sn.pub/extras

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

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xviii
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  2. Design of Static Metaheuristics for Medical Image Analysis

    • Amir Nakib
    Pages 1-22

  3. Multi-level Image Thresholding Based on Hybrid Differential Evolution Algorithm. Application on Medical Images

    • M. Ali, P. Siarry, M. Pant
    Pages 23-36

  4. Fuzzy Edge Detection in Computed Tomography Through Genetic Algorithm Optimization

    • A. M. T. Gouicem, M. Yahi, A. Taleb-Ahmed
    Pages 37-47

  5. Particle Swarm Optimization Based Fast Chan-Vese Algorithm for Medical Image Segmentation

    • Devraj Mandal, Amitava Chatterjee, Madhubanti Maitra
    Pages 49-74

  6. Evidential Deformable Model for Contour Tracking. Application on Brain Cine MR Sequences

    • Sarra Naffakhi, Amir Nakib, Atef Hamouda
    Pages 75-107

  7. Microscopic Image Segmentation Based on Based Branch and Bound and Game Theory

    • Amira Kouzana, Amir Nakib, Narjes Dogaz
    Pages 109-120

  8. Dynamic Metaheuristics for Brain Cine-MRI

    • Amir Nakib
    Pages 121-135

  9. Lexicographic Approach Based on Evidence Theory for Blood Cell Image Segmentation

    • Ismahan Baghli, Amir Nakib
    Pages 137-154

  10. Medical Image Denoising Using Metaheuristics

    • Serdar Kockanat, Nurhan Karaboga
    Pages 155-169

  11. Medical Image Registration Based on Metaheuristics: A Comparative Study

    • A. Nakib, E.-G. Talbi, S. Corniglion
    Pages 171-185

  12. Adaptive ECG Signal Filtering Using Bayesian Based Evolutionary Algorithm

    • Thibaut Bernard, Amir Nakib
    Pages 187-211
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Keywords

About this book

This book highlights recent research on metaheuristics for biomedical engineering, addressing both theoretical and applications aspects. Given the multidisciplinary nature of bio-medical image analysis, it has now become one of the most central topics in computer science, computer engineering and electrical and electronic engineering, and attracted the interest of many researchers.

To deal with these problems, many traditional and recent methods, algorithms and techniques have been proposed. Among them, metaheuristics is the most common choice. This book provides essential content for senior and young researchers interested in methodologies for implementing metaheuristics to help solve biomedical engineering problems.

Editors and Affiliations

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

    Amir Nakib

  • 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

Bibliographic Information

  • Book Title: Metaheuristics for Medicine and Biology

  • Editors: Amir Nakib, El-Ghazali Talbi

  • Series Title: Studies in Computational Intelligence

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

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag GmbH Germany 2017

  • Hardcover ISBN: 978-3-662-54426-6Published: 30 March 2017

  • Softcover ISBN: 978-3-662-57196-5Published: 25 July 2018

  • eBook ISBN: 978-3-662-54428-0Published: 22 March 2017

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XVIII, 211

  • Number of Illustrations: 53 b/w illustrations, 67 illustrations in colour

  • Topics: Computational Intelligence, Biomedical Engineering and Bioengineering, Artificial Intelligence

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