IDEAS home Printed from https://ideas.repec.org/a/igg/jncr00/v8y2019i3p41-54.html
   My bibliography  Save this article

A Comparative Objective Assessment on Mesh-Based and SVM-Based 3D Reconstruction of MRI Brain

Author

Listed:
  • Sushitha Susan Joseph

    (Vellore Institute of Technology, Vellore, India)

  • Aju D.

    (Vellore Institute of Technology, Vellore, India)

Abstract

Three-dimensional reconstruction is the process of acquiring the volumetric information from two dimensions, converting and representing it in three dimensions. The reconstructed images play a vital role in the disease diagnosis, treatment and surgery. Brain surgery is one of the main treatment options following the diagnosis of brain damage. The risk associated with brain surgery is high. Reconstructed brain images help the surgeons to visualize the exact location of tumor, plan and perform the surgical procedures from craniotomy to tumor resection with high precision. This survey provides an overview of the three-dimensional reconstruction techniques in MRI brain and brain tumors. The triangle generation methods and support vector machine methods are briefly described. The advantages and disadvantages of each method is discussed. The comparison reveals that Immune Sphere Shaped Support Vector Machine is the best choice when execution time is considered and triangle mesh generation algorithm is the best when visual quality is considered.

Suggested Citation

  • Sushitha Susan Joseph & Aju D., 2019. "A Comparative Objective Assessment on Mesh-Based and SVM-Based 3D Reconstruction of MRI Brain," International Journal of Natural Computing Research (IJNCR), IGI Global, vol. 8(3), pages 41-54, July.
  • Handle: RePEc:igg:jncr00:v:8:y:2019:i:3:p:41-54
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJNCR.2019070103
    Download Restriction: no
    ---><---

    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:igg:jncr00:v:8:y:2019:i:3:p:41-54. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.