IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0113405.html
   My bibliography  Save this article

Lipid Vesicle Shape Analysis from Populations Using Light Video Microscopy and Computer Vision

Author

Listed:
  • Jernej Zupanc
  • Barbara Drašler
  • Sabina Boljte
  • Veronika Kralj-Iglič
  • Aleš Iglič
  • Deniz Erdogmus
  • Damjana Drobne

Abstract

We present a method for giant lipid vesicle shape analysis that combines manually guided large-scale video microscopy and computer vision algorithms to enable analyzing vesicle populations. The method retains the benefits of light microscopy and enables non-destructive analysis of vesicles from suspensions containing up to several thousands of lipid vesicles (1–50 µm in diameter). For each sample, image analysis was employed to extract data on vesicle quantity and size distributions of their projected diameters and isoperimetric quotients (measure of contour roundness). This process enables a comparison of samples from the same population over time, or the comparison of a treated population to a control. Although vesicles in suspensions are heterogeneous in sizes and shapes and have distinctively non-homogeneous distribution throughout the suspension, this method allows for the capture and analysis of repeatable vesicle samples that are representative of the population inspected.

Suggested Citation

  • Jernej Zupanc & Barbara Drašler & Sabina Boljte & Veronika Kralj-Iglič & Aleš Iglič & Deniz Erdogmus & Damjana Drobne, 2014. "Lipid Vesicle Shape Analysis from Populations Using Light Video Microscopy and Computer Vision," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-14, November.
    • Handle: RePEc:plo:pone00:0113405
    DOI: 10.1371/journal.pone.0113405
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0113405
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0113405&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0113405?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:pone00:0113405. 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.