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This paper describes an automatic technique to segment the ventricles from brain MRI of young children. The segmentation approach involves skull stripping, extraction of the total cerebrospinal fluid (CSF), isolation of extra-cerebral CSF, removal of CSF in the sulci and fissures and final ventricle segmentation. The segmentation achieves a mean Dice ratio of 0.9246, sensitivity of 0.9363 and specificity...
The automated tissue classification of pediatric brain magnetic resonance images, specially proper segmentation of myelinated white matter, is a highly challenging task. The proposed approach first extracts the brain tissue, followed by a precise delineation of the myelinated component based on Tsallis entropy segmentation. Unlike most of the currently available algorithms, the proposed technique...
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