A new method to segment the multiple sclerosis lesions on brain magnetic resonance images
A Karimian, S Jafari - Journal of Medical Signals & Sensors, 2015 - journals.lww.com
Automatic segmentation of multiple sclerosis (MS) lesions in brain magnetic resonance
imaging (MRI) has been widely investigated in the recent years with the goal of helping MS
diagnosis and patient follow-up. In this research work, Gaussian mixture model (GMM) has
been used to segment the MS lesions in MRIs, including T1-weighted (T1-w), T2-w, and T2-
fluid attenuation inversion recovery. Usually, GMM is optimized by using expectation-
maximization (EM) algorithm. The drawbacks of this optimization method are, it does not …
imaging (MRI) has been widely investigated in the recent years with the goal of helping MS
diagnosis and patient follow-up. In this research work, Gaussian mixture model (GMM) has
been used to segment the MS lesions in MRIs, including T1-weighted (T1-w), T2-w, and T2-
fluid attenuation inversion recovery. Usually, GMM is optimized by using expectation-
maximization (EM) algorithm. The drawbacks of this optimization method are, it does not …
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