1 citations · 1 across the 3 of their papers we have counts for
3 papers
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…
Geometric Deep Learning for the Assessment of Thrombosis Risk in the Left Atrial Appendage
Xabier Morales, Jordi Mill, Guillem Simeon +4
The assessment of left atrial appendage (LAA) thrombogenesis has experienced major advances with the adoption of patient-specific computational fluid dynamics (CFD) simulations. No…
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…