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Boosting Skull-Stripping Performance for Pediatric Brain Images
With the emergence of multi-institutional pediatric data acquisition efforts to broaden the understanding of perinatal brain development, it is essential to develop robust and well-tested tools ready for the relevant data processing.
VINNA for Neonates -- Orientation Independence through Latent Augmentations
However, these transformations in the image space still require resampling, reducing accuracy specifically in the context of label interpolation.
Automating Whole Brain Histology to MRI Registration: Implementation of a Computational Pipeline
In this paper we report the accuracy of our pipeline in two whole brain volumes from the Brain Bank of the Brazilian Aging Brain Study Group (BBBABSG).
Fast Infant MRI Skullstripping with Multiview 2D Convolutional Neural Networks
The three probabilistic segmentations in the three views are linearly fused and thresholded to produce a final brain mask.
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