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Multiscale Approach for Multiple Sclerosis Lesion in Multichannel MRI


Affiliations
1 Department of Computer Science and Engineering, Dr. Sivanthi Adithanar College of Engineering, Tiruchendur-628215, India
2 Computer Science and Engineering, Dr. Sivanthi Adithanar College of Engineering, Tiruchendur-628215, India
     

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The multiscale approach that combines segmentation with classification to detect abnormal brain structures in medical imagery, and demonstrate its utility by automatically detecting multiple sclerosis (MS) lesions in 3-D multichannel magnetic resonance (MR) images. Our method uses segmentation to obtain a hierarchical decomposition of a multichannel, anisotropic MR scans. It then produces a rich set of features describing the segments in terms of intensity, shape, location, neighborhood relations, and anatomical context. These features are used in the Machine Learning;from this we can get the fully automatic, efficient results.

Keywords

Brain Imaging, MRI, Multiple Sclerosis, Segmentation.
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  • Multiscale Approach for Multiple Sclerosis Lesion in Multichannel MRI

Abstract Views: 140  |  PDF Views: 2

Authors

S. Thivya
Department of Computer Science and Engineering, Dr. Sivanthi Adithanar College of Engineering, Tiruchendur-628215, India
G. Wiselin Jiji
Computer Science and Engineering, Dr. Sivanthi Adithanar College of Engineering, Tiruchendur-628215, India

Abstract


The multiscale approach that combines segmentation with classification to detect abnormal brain structures in medical imagery, and demonstrate its utility by automatically detecting multiple sclerosis (MS) lesions in 3-D multichannel magnetic resonance (MR) images. Our method uses segmentation to obtain a hierarchical decomposition of a multichannel, anisotropic MR scans. It then produces a rich set of features describing the segments in terms of intensity, shape, location, neighborhood relations, and anatomical context. These features are used in the Machine Learning;from this we can get the fully automatic, efficient results.

Keywords


Brain Imaging, MRI, Multiple Sclerosis, Segmentation.