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Abstract #3413

Can brain MRI skull-stripping methods be further improved using manual segmentation as ground-truth for validation?

Roberto Souza1, Oeslle Lucena2, Letícia Rittner2, Roberto Lotufo2, and Richard Frayne1

1Seaman Family Magnetic Resonance Research Centre, Calgary, AB, Canada, 2Medical Image Computing Lab, Campinas, Brazil

Automatic skull-stripping (SS) methods have reached a high level of accuracy compared to expert manual segmentation (typically defined as the “ground-truth”), but SS is still an active research area with many methods being proposed every year. In this work, we use twelve T1-weighted brain magnetic resonance (MR) images with each image having two different manual segmentations performed by experts, and four state-of-the-art SS methods to assess if it is possible to evaluate further accuracy improvements to SS. Our results indicate that at the current level of SS accuracy, this is not possible using single expert manual segmentation.

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