35 citations · 49 across the 7 of their papers we have counts for
3 papers · 1 filter
NUDF: Neural Unsigned Distance Fields for high resolution 3D medical image segmentation
Kristine Sørensen, Oscar Camara, Ole de Backer +2
Medical image segmentation is often considered as the task of labelling each pixel or voxel as being inside or outside a given anatomy. Processing the images at their original size…
Multi-modal data generation with a deep metric variational autoencoder
Josefine Vilsbøll Sundgaard, Morten Rieger Hannemose, Søren Laugesen +6
We present a deep metric variational autoencoder for multi-modal data generation. The variational autoencoder employs triplet loss in the latent space, which allows for conditional…
Guiding 3D U-nets with signed distance fields for creating 3D models from images
Kristine Aavild Juhl, Rasmus Reinhold Paulsen, Anders Bjorholm Dahl +4
Morphological analysis of the left atrial appendage is an important tool to assess risk of ischemic stroke. Most deep learning approaches for 3D segmentation is guided by binary la…