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

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Metaheuristics for Medicine and Biology

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

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Abstract

The goal of this paper is to introduce an efficient evidential particle filter for complex shapes tracking. The particularity of that particle filter is not only the fair use of the observation at the current time in the update step of it by performing a curve evolution but also it represents a bridge between Probability function and Evidence theory. This bridge can be illustrated by incorporating a data fusion step in the update phase. This method builds a track by selecting the best particles between the particle candidates. This re-sampling phase is based on choosing the particles possessing the higher value of the basic belief assignment function. The values of these basic belief assignment functions are resulting from the fusion process of two distinctive sources of information. The first source is the energy functional and the second one is the local sensitive histogram. The evaluation of our approach, which is made on a realistic Brain cine RM sequences, aims at tracking the motion of the walls of the third ventricle. Therefore, the latter shows its obvious and clear efficiency. In order to validate our proposal, we present a comparative study between our proposal and the state of the art methods. The obtained results are encouraging.

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Author information

Authors and Affiliations

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

    Sarra Naffakhi & Amir Nakib

  2. LIPAH, FST, University Tunis El Manar, Tunis, Tunisia

    Sarra Naffakhi & Atef Hamouda

Authors
  1. Sarra Naffakhi
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  2. Amir Nakib
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  3. Atef Hamouda
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Corresponding author

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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Naffakhi, S., Nakib, A., Hamouda, A. (2017). Evidential Deformable Model for Contour Tracking. Application on Brain Cine MR Sequences. 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_5

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  • DOI: https://doi.org/10.1007/978-3-662-54428-0_5

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