IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0067418.html
   My bibliography  Save this article

A Magnetic Resonance Image Based Atlas of the Rabbit Brain for Automatic Parcellation

Author

Listed:
  • Emma Muñoz-Moreno
  • Ariadna Arbat-Plana
  • Dafnis Batalle
  • Guadalupe Soria
  • Miriam Illa
  • Alberto Prats-Galino
  • Elisenda Eixarch
  • Eduard Gratacos

Abstract

Rabbit brain has been used in several works for the analysis of neurodevelopment. However, there are not specific digital rabbit brain atlases that allow an automatic identification of brain regions, which is a crucial step for various neuroimage analyses, and, instead, manual delineation of areas of interest must be performed in order to evaluate a specific structure. For this reason, we propose an atlas of the rabbit brain based on magnetic resonance imaging, including both structural and diffusion weighted, that can be used for the automatic parcellation of the rabbit brain. Ten individual atlases, as well as an average template and probabilistic maps of the anatomical regions were built. In addition, an example of automatic segmentation based on this atlas is described.

Suggested Citation

  • Emma Muñoz-Moreno & Ariadna Arbat-Plana & Dafnis Batalle & Guadalupe Soria & Miriam Illa & Alberto Prats-Galino & Elisenda Eixarch & Eduard Gratacos, 2013. "A Magnetic Resonance Image Based Atlas of the Rabbit Brain for Automatic Parcellation," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-13, July.
    • Handle: RePEc:plo:pone00:0067418
    DOI: 10.1371/journal.pone.0067418
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0067418
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0067418&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0067418?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:pone00:0067418. 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.