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

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

Amina Merzoug, Nacéra Benamrane, Abdelmalik Taleb-Ahmed
Copyright: © 2021 |Pages: 14
DOI: 10.4018/IJCINI.20210401.oa8
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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.
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The Proposed Approach

Automatic segmentation of MS lesions is difficult, as indicated in the previous section due to the large variability of multiple sclerosis lesions. Lesions have deformable shapes, their texture and intensity can vary and their location can also vary from one patient to another. The researchers propose to apply a new segmentation workflow based on a voxel analysis.

The method consists of three steps (see Figure 1). For each 3D MR image, the AIS are applied for segmentation of the three main brain tissues white matter, gray matter and cerebrospinal fluid. The authors compute a number of features then the SVM is used for MS lesions segmentation only on the white matter since MS lesions are located in.

Figure 1.

Flowchart of the proposed approach for MS lesions segmentation

IJCINI.20210401.oa8.f01

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