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Found 4 papers, 2 papers with code
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.
Identifying and Combating Bias in Segmentation Networks by leveraging multiple resolutions
We analyse how this resolution-bias in the data distribution propagates to systematically biased predictions for group L at higher resolutions.
FastSurferVINN: Building Resolution-Independence into Deep Learning Segmentation Methods -- A Solution for HighRes Brain MRI
Leading neuroimaging studies have pushed 3T MRI acquisition resolutions below 1. 0 mm for improved structure definition and morphometry.
FastSurfer -- A fast and accurate deep learning based neuroimaging pipeline
In this work we propose a fast and accurate deep learning based neuroimaging pipeline for the automated processing of structural human brain MRI scans, replicating FreeSurfer's anatomical segmentation including surface reconstruction and cortical parcellation.
