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Segmentation of Pathology in Tumor-Diseased Brains | ||
| Journal of Engineering and Sustainable Development | ||
| Article 1, Volume 12, Issue 2, 2008, Pages 101-110 | ||
| Author | ||
| Mohammed Hatim Khdair | ||
| Abstract | ||
| Automatic segmentation of multiple sclerosis lesions in magnetic resonance images remains a challenging task. In this study, we present a fully automatic method to extract lesions from multi-sequence MRI (T1, T2, T2 FLAIR, Proton Density) within an Expectation Maximization (EM) based probabilistic framework.The method uses the available MRI sequences in a hierarchical, orderly manner. First the T2 FLAIR sequence is used to generate a segmentation of supra-tentorial lesions. Then T2 and T1 lesion loads are computed, providing an insight into lesion structure | ||
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