35 citations · 38 across the 5 of their papers we have counts for
5 papers
Signed Distance Field based Segmentation and Statistical Shape Modelling of the Left Atrial Appendage
Kristine Aavild Juhl, Jakob Slipsager, Ole de Backer +3
Patients with atrial fibrillation have a 5-7 fold increased risk of having an ischemic stroke. In these cases, the most common site of thrombus localization is inside the left atri…
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…
EyeLoveGAN: Exploiting domain-shifts to boost network learning with cycleGANs
Josefine Vilsbøll Sundgaard, Kristine Aavild Juhl, Jakob Mølkjær Slipsager
This paper presents our contribution to the REFUGE challenge 2020. The challenge consisted of three tasks based on a dataset of retinal images: Segmentation of optic disc and cup,…
Multi-view consensus CNN for 3D facial landmark placement
Rasmus R. Paulsen, Kristine Aavild Juhl, Thilde Marie Haspang +3
The rapid increase in the availability of accurate 3D scanning devices has moved facial recognition and analysis into the 3D domain. 3D facial landmarks are often used as a simple…
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…