Improved subcortical segmentation using multiple MR modalities

Automated segmentation of subcortical structures is typically performed using T1-weighted volumes. However, not all of these structures' boundaries are clearly visible with T1 contrast. We describe a multimodal segmentation method that integrates information from different contrasts: in this case T1-weighted, T2-weighted and FA volumes. Since the images contain complementary information, the method does not need to rely heavily on prior shape knowledge obtained from training data. We show that, in specific areas, the method performs considerably better than FIRST, a segmentation method that only uses T1-weighted volumes.

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