Lesions Detection of Multiple Sclerosis in 3D Brian MR Images by Using Artificial Immune Systems and Support Vector Machines

Amina Merzoug, Nacéra Benamrane and Abdelmalik Taleb-Ahmed
Additional contact information
Amina Merzoug: Laboratoire SIMPA, USTO-MB, Bir El Djir, Algeria
Nacéra Benamrane: Laboratoire SIMPA, USTO-MB, Bir El Djir, Algeria
Abdelmalik Taleb-Ahmed: Polytechnic University of Hauts-de-France, Valenciennes, France

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2021, vol. 15, issue 2, 97-110

Abstract: This paper presents a segmentation method to detect multiple sclerosis (MS) lesions in brain MRI based on the artificial immune systems (AIS) and a support vector machines (SVM). In the first step, AIS is used to segment the three main brain tissues white matter, gray matter, and cerebrospinal fluid. Then the features were extracted and SVM is applied to detect the multiple sclerosis lesions based on SMO training algorithm. The experiments conducted on 3D brain MR images produce satisfying results.

Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... /IJCINI.20210401.oa8 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jcini0:v:15:y:2021:i:2:p:97-110

Access Statistics for this article

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) is currently edited by Kangshun Li

More articles in International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) from IGI Global
Bibliographic data for series maintained by Journal Editor ().