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Performance Evaluation of Segmentation Algorithms Based on Level Set Method: Application to Medical Images

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Recent Advances in Electrical Engineering and Control Applications (ICEECA 2016)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 411))

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Abstract

Currently, the phase of segmentation is an important step in the treatment and the interpretation of the medical images; it represents one of the most difficult step for the extraction of the relevant parameters of the image and fact part of a very active field and rich of research. In this paper, we present an overview about segmentation methods based on level set technique, namely Caselle method, Chan Vese method, Chumming Li method, Lankton method, Bernard method and Shi method. The performance of each method can be evaluated either visually, or from similarity measurements between a reference and the results of the segmentation. We have applied each method for different medical images. We present a comparative evaluation of the considered segmentation methods, with respect to four criteria, given specific medical datasets. Through simulated results, we have demonstrated that the best results are achieved by Shi method and Chan & Vese method.

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Author information

Authors and Affiliations

  1. Science and Technology Department, University of Batna, Batna, Algeria

    Messaouda Larbi

  2. Science and Technology Department, University of Bordj Bou Arreridj, El Anasser, Bordj Bou Arreridj, Algeria

    Zoubeida Messali

  3. Laboratoire de Génie Electrique LGE, M’sila, Algeria

    Zoubeida Messali

Authors
  1. Messaouda Larbi
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  2. Zoubeida Messali
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Corresponding author

Correspondence to Messaouda Larbi .

Editor information

Editors and Affiliations

  1. MIS (EA 4290), Université de Picardie Jules Verne, Amiens, France

    Mohammed Chadli

  2. Laboratoire d'Automatique et de Robotiqu, Université Abbes Laghrour, Khenchela, Khenchela, Algeria

    Sofiane Bououden

  3. VŠB-Technical University of Ostrava , Ostrava ba, Czech Republic

    Ivan Zelinka

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Larbi, M., Messali, Z. (2017). Performance Evaluation of Segmentation Algorithms Based on Level Set Method: Application to Medical Images. In: Chadli, M., Bououden, S., Zelinka, I. (eds) Recent Advances in Electrical Engineering and Control Applications. ICEECA 2016. Lecture Notes in Electrical Engineering, vol 411. Springer, Cham. https://doi.org/10.1007/978-3-319-48929-2_29

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  • DOI: https://doi.org/10.1007/978-3-319-48929-2_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48928-5

  • Online ISBN: 978-3-319-48929-2

  • eBook Packages: EngineeringEngineering (R0)

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