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Complex System Modelling and Control Through Intelligent Soft Computations pp 139–163Cite as

Leukocyte Detection Through an Evolutionary Method

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 319))

Abstract

Classical image processing methods often face great difficulties while dealing with images containing noise and distortions. Under such conditions, the use of soft computing approaches has been recently extended to address challenging real-world image processing problems. The automatic detection of Leukocytes or White Blood Cells (WBC) still remains as an unsolved issue in medical imaging. The analysis of WBC images has engaged researchers from fields of medicine and image processing alike. Since WBC can be approximated by an ellipsoid form, an ellipse detector algorithm may be successfully applied in order to recognize such elements. This chapter presents an algorithm for the automatic detection of leukocytes embedded into complicated and cluttered smear images that considers the complete process as a multi-ellipse detection problem. The approach, which is based on the Differential Evolution (DE) algorithm, transforms the detection task into an optimization problem whose individuals represent candidate ellipses. An objective function evaluates if such candidate ellipses are actually present in the edge map of the smear image. Guided by the values of such function, the set of encoded candidate ellipses (individuals) are evolved using the DE algorithm so that they can fit into the leukocytes which are enclosed within the edge map of the smear image. Experimental results from white blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique in terms of its accuracy and robustness.

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Author information

Authors and Affiliations

  1. Departamento de Electrónica, CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

    Erik Cuevas

  2. División de Biotecnología y Salud, ITESM, Campus Guadalajara, Zapopan, Mexico

    Margarita Díaz

  3. Institut Für Informatik, Freie Universität Berlin, Berlin, Germany

    Raúl Rojas

Authors
  1. Erik Cuevas
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  2. Margarita Díaz
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  3. Raúl Rojas
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Corresponding author

Correspondence to Erik Cuevas .

Editor information

Editors and Affiliations

  1. Department of Engineering Design and Mathematics, University of the West of England, Bristol, United Kingdom

    Quanmin Zhu

  2. Faculty of Computers and Information, Benha University, Benha, Egypt

    Ahmad Taher Azar

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Cuevas, E., Díaz, M., Rojas, R. (2015). Leukocyte Detection Through an Evolutionary Method. In: Zhu, Q., Azar, A. (eds) Complex System Modelling and Control Through Intelligent Soft Computations. Studies in Fuzziness and Soft Computing, vol 319. Springer, Cham. https://doi.org/10.1007/978-3-319-12883-2_5

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  • DOI: https://doi.org/10.1007/978-3-319-12883-2_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12882-5

  • Online ISBN: 978-3-319-12883-2

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