MS lesions segmentation in 3D MR images using FCM and SVM

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

“…The Figures 2, 3, 4 and 5 show the obtained results of AIS approach. Figures 2(1), 3(1), 4(1), and 5(1) show the original images, Figures 2(2), 2 3), 2(4); 3(2), 3(3), 3(4), 4(2), 4(3), 4(4) and 5(2 They have compared the proposed approach with their previous approach (Merzoug et al, 2014) and another method which segments multiple sclerosis (MS) lesions in WM using a modified algorithm that relies on the histo based fast fuzzy C-means (HFFCM) (Yaswanth et al, 2016) using 3D simulated MR data (brainweb). Table 1 shows the results of a comparison between the proposed approach and other techniques for detecting multiple sclerosis lesions.…”

“…They have compared the proposed approach with their previous approach (Merzoug et al, 2014) and another method which segments multiple sclerosis (MS) lesions in WM using a modified algorithm that relies on the histo based fast fuzzy C-means (HFFCM) (Yaswanth et al, 2016) using 3D simulated MR data (brainweb).…”

“…Various feature extraction methods has been proposed in the literature using first statistical texture features (Faro et al, 2010). As mentioned in a previous work (Merzoug et al, 2014), MS lesions appear hypo-or hyper-signal compared to the normal appearing white matter according to their type and MRI sequences. They define vector types of specific lesions.…”