IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0006010.html
   My bibliography  Save this article

Understanding Physiological and Degenerative Natural Vision Mechanisms to Define Contrast and Contour Operators

Author

Listed:
  • Jacques Demongeot
  • Yannick Fouquet
  • Muhammad Tayyab
  • Nicolas Vuillerme

Abstract

Background: Dynamical systems like neural networks based on lateral inhibition have a large field of applications in image processing, robotics and morphogenesis modeling. In this paper, we will propose some examples of dynamical flows used in image contrasting and contouring. Methodology: First we present the physiological basis of the retina function by showing the role of the lateral inhibition in the optical illusions and pathologic processes generation. Then, based on these biological considerations about the real vision mechanisms, we study an enhancement method for contrasting medical images, using either a discrete neural network approach, or its continuous version, i.e. a non-isotropic diffusion reaction partial differential system. Following this, we introduce other continuous operators based on similar biomimetic approaches: a chemotactic contrasting method, a viability contouring algorithm and an attentional focus operator. Then, we introduce the new notion of mixed potential Hamiltonian flows; we compare it with the watershed method and we use it for contouring. Conclusions: We conclude by showing the utility of these biomimetic methods with some examples of application in medical imaging and computed assisted surgery.

Suggested Citation

  • Jacques Demongeot & Yannick Fouquet & Muhammad Tayyab & Nicolas Vuillerme, 2009. "Understanding Physiological and Degenerative Natural Vision Mechanisms to Define Contrast and Contour Operators," PLOS ONE, Public Library of Science, vol. 4(6), pages 1-17, June.
  • Handle: RePEc:plo:pone00:0006010
    DOI: 10.1371/journal.pone.0006010
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0006010
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0006010&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0006010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0006010. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.