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Found 10 papers, 4 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.
FastSurfer-HypVINN: Automated sub-segmentation of the hypothalamus and adjacent structures on high-resolutional brain MRI
The hypothalamus plays a crucial role in the regulation of a broad range of physiological, behavioural, and cognitive functions.
Estimating Head Motion from MR-Images
Head motion is an omnipresent confounder of magnetic resonance image (MRI) analyses as it systematically affects morphometric measurements, even when visual quality control is performed.
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.
Learning Anatomical Segmentations for Tractography from Diffusion MRI
Here, we introduce fast, deep learning-based segmentation of 170 anatomical regions directly on diffusion-weighted MR images, removing the dependency of conventional segmentation methods on T 1-weighted images and slow pre-processing pipelines.
AutoSNAP: Automatically Learning Neural Architectures for Instrument Pose Estimation
Despite recent successes, the advances in Deep Learning have not yet been fully translated to Computer Assisted Intervention (CAI) problems such as pose estimation of surgical instruments.
Exploring Adversarial Examples: Patterns of One-Pixel Attacks
Failure cases of black-box deep learning, e. g. adversarial examples, might have severe consequences in healthcare.
How Bad is Good enough: Noisy annotations for instrument pose estimation
In the application of surgical instrument pose estimation, where precision has a direct clinical impact on patient outcome, studying the effect of \emph{noisy annotations} on deep learning pose estimation techniques is of supreme importance.
i3PosNet: Instrument Pose Estimation from X-Ray in temporal bone surgery
Purpose: Accurate estimation of the position and orientation (pose) of surgical instruments is crucial for delicate minimally invasive temporal bone surgery.
