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Background and objective The volume of the intracerebral hemorrhage (ICH) obtained from CT scans is essential for quantification and treatment planning. However,a fast and accurate volume acquisition brings great challenges. On the one hand, it is both time consuming and operator dependent for manual segmentation, which is the gold standard for volume estimation. On the other hand, low contrast to normal tissues, irregular shapes and distributions of the hemorrhage make the existing automatic segmentation methods hard to achieve satisfacto
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