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Automatic Fitting of Feature Points for Border Detection of Skin Lesions in Medical Images with Bat Algorithm

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Intelligent Distributed Computing XII (IDC 2018)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 798))

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Abstract

This paper addresses the problem of automatic fitting of feature points for border detection of skin lesions. This problem is an important task in segmentation of dermoscopy images for semi-automatic early diagnosis of melanoma and other skin lesions. Given a set of feature points selected by a dermatologist, we apply a powerful nature-inspired metaheuristic optimization method called bat algorithm to obtain the free-form parametric Bézier curve that fits the points better in the least-squares sense. Our experimental results on two examples of skin lesions show that the method performs quite well and might be applied to automatic fitting of feature points for border detection in medical images.

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Acknowledgments

This research work has been kindly supported by the project PDE-GIR of the European Union’s Horizon 2020 research and innovation programme, Marie Sklodowska-Curie grant agreement No 778035, the Spanish Ministry of Economy and Competitiveness (Computer Science National Program), grant #TIN2017-89275-R of the Agencia Estatal de Investigación and European Regional Development Funds (AEI/FEDER-UE), the project #JU12 of SODERCAN and European Regional Development Funds (SODERCAN/FEDER-UE), the Slovenian Research Agency (Research Core Funding No. P2-0057), and the project EMAITEK of the Basque Government.

Author information

Authors and Affiliations

  1. Toho University, 2-2-1 Miyama, Funabashi, 274-8510, Japan

    Akemi Gálvez & Andrés Iglesias

  2. Universidad de Cantabria, Avda. de los Castros, s/n, 39005, Santander, Spain

    Akemi Gálvez & Andrés Iglesias

  3. University of Maribor, Smetanova, Maribor, Slovenia

    Iztok Fister & Iztok Fister Jr.

  4. TECNALIA, Derio, Spain

    Eneko Osaba & Javier Del Ser

  5. University of the Basque Country (UPV/EHU), Bilbao, Spain

    Javier Del Ser

  6. Basque Center for Applied Mathematics (BCAM), Bilbao, Spain

    Javier Del Ser

Authors
  1. Akemi Gálvez
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  2. Iztok Fister
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  3. Iztok Fister Jr.
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  4. Eneko Osaba
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  5. Javier Del Ser
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  6. Andrés Iglesias
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Corresponding author

Correspondence to Andrés Iglesias .

Editor information

Editors and Affiliations

  1. Basque Center for Applied Mathematics (BCAM), TECNALIA, University of the Basque Country (UPV/EHU), Derio, Bizkaia, Spain

    Javier Del Ser

  2. TECNALIA, Derio, Bizkaia, Spain

    Eneko Osaba

  3. University of the Basque Country (UPV/EHU), Bilbao, Bizkaia, Spain

    Miren Nekane Bilbao

  4. Computer Science Department, University of Las Palmas de Gran Canaria, Las Palmas, Spain

    Javier J. Sanchez-Medina

  5. OpenIoT Reesarch Unit, FBK CREATE-NET, Trento, Italy

    Massimo Vecchio

  6. Department of Design Engineering and Mathematics, Middlesex University, London, UK

    Xin-She Yang

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Gálvez, A., Fister, I., Fister, I., Osaba, E., Del Ser, J., Iglesias, A. (2018). Automatic Fitting of Feature Points for Border Detection of Skin Lesions in Medical Images with Bat Algorithm. In: Del Ser, J., Osaba, E., Bilbao, M., Sanchez-Medina, J., Vecchio, M., Yang, XS. (eds) Intelligent Distributed Computing XII. IDC 2018. Studies in Computational Intelligence, vol 798. Springer, Cham. https://doi.org/10.1007/978-3-319-99626-4_31

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  • DOI: https://doi.org/10.1007/978-3-319-99626-4_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99625-7

  • Online ISBN: 978-3-319-99626-4

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