IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v8y2017i2d10.1007_s13198-016-0465-8.html
   My bibliography  Save this article

A proposed quantitative approach to classify brain MRI

Author

Listed:
  • Madhulika Bhatia

    (Amity University)

  • Abhay Bansal

    (Amity University)

  • Divakar Yadav

    (Jaypee University)

Abstract

Analysis of magnetic resonance images of brain is done statistically using t test in excel and SPSS. The methodology would help the medical specialists to mechanize the examination of MRI’s of brain to differentiate the tumor from non tumor pictures to upgrade the therapeutic medical considerations. Tumor brain images can be classified from non tumor brain MRI images using a novel approach which detect grey matter in MRI images. The basic images preprocessing steps are followed like displaying of grey matter, segmentation, grey matter extraction and all is executed in Matlab environment. Statistical technique like t test in excel and SPSS is performed for classification of brain MRI images on the basis of grey matter extracted is done using Matlab. Our novel approach uses the benefits of existing preprocessing methods and filters available in Matlab for effectual extraction and analysis of brain MRI images. The work has been tested on 50 variables on forty-six subjects. Out of forty-six, twenty-four belong to healthy group and rest twenty-two belong to unhealthy. The work is assessed using t test in SPSS. The brain images are taken from the BRAINIX database and neuroimaging data repository. The proposed algorithm will be an easy approach for doctors and physicians to provide easy option for medical image analysis.

Suggested Citation

  • Madhulika Bhatia & Abhay Bansal & Divakar Yadav, 2017. "A proposed quantitative approach to classify brain MRI," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 577-584, November.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-016-0465-8
    DOI: 10.1007/s13198-016-0465-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-016-0465-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-016-0465-8?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-016-0465-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.