| Multi-view consensus CNN for 3D facial landmark placement RR Paulsen, KA Juhl, TM Haspang, T Hansen, M Ganz, G Einarsson Asian Conference on Computer Vision, 706-719, 2018 | 46 | 2018 |
| Deep Learning Framework for Real-Time Estimation of in-silico Thrombotic Risk Indices in the Left Atrial Appendage X Morales Ferez, J Mill, KA Juhl, C Acebes, X Iriart, B Legghe, H Cochet, ... Frontiers in Physiology 12, 694945, 2021 | 44 | 2021 |
| Deep learning surrogate of computational fluid dynamics for thrombus formation risk in the left atrial appendage X Morales, J Mill, KA Juhl, A Olivares, G Jimenez-Perez, RR Paulsen, ... Statistical Atlases and Computational Models of the Heart. Multi-Sequence …, 2020 | 24 | 2020 |
| Statistical shape clustering of left atrial appendages JM Slipsager, KA Juhl, PE Sigvardsen, KF Kofoed, O De Backer, ... Statistical Atlases and Computational Models of the Heart. Atrial …, 2019 | 13 | 2019 |
| NUDF: neural unsigned distance fields for high resolution 3D medical image segmentation K Sørensen, O Camara, O De Backer, KF Kofoed, RR Paulsen 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 1-5, 2022 | 7 | 2022 |
| Implicit neural distance representation for unsupervised and supervised classification of complex anatomies KA Juhl, X Morales, O De Backer, O Camara, RR Paulsen Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 7 | 2021 |
| Deep reinforcement learning for detection of inner ear abnormal anatomy in computed tomography P López Diez, K Sørensen, JV Sundgaard, K Diab, J Margeta, F Patou, ... International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 6 | 2022 |
| Deep reinforcement learning for detection of abnormal anatomies PL Diez, KA Juhl, JV Sundgaard, H Diab, J Margeta, F Patou, RR Paulsen Proceedings of the Northern Lights Deep Learning Workshop 3, 2022 | 6 | 2022 |
| Multi-planar whole heart segmentation of 3D CT images using 2D spatial propagation CNN JV Sundgaard, KA Juhl, KF Kofoed, RR Paulsen Medical Imaging 2020: Image Processing 11313, 477-484, 2020 | 5 | 2020 |
| Guiding 3D U-nets with signed distance fields for creating 3D models from images KA Juhl, RR Paulsen, AB Dahl, VA Dahl, O De Backer, KF Kofoed, ... arXiv preprint arXiv:1908.10579, 2019 | 5 | 2019 |
| Signed distance field based segmentation and statistical shape modelling of the left atrial appendage KA Juhl, J Slipsager, O De Backer, K Kofoed, O Camara, R Paulsen arXiv preprint arXiv:2402.07708, 2024 | 2 | 2024 |
| SparseMeshCNN with self-attention for segmentation of large meshes B Hansen, M Lowes, T Ørkild, A Dahl, V Dahl, O De Backer, O Camara, ... Proceedings of the Northern Lights Deep Learning Workshop 3, 2022 | 2 | 2022 |
| Geometric deep learning for the assessment of thrombosis risk in the left atrial appendage X Morales, J Mill, G Simeon, KA Juhl, O De Backer, RR Paulsen, ... International Conference on Functional Imaging and Modeling of the Heart …, 2021 | 2 | 2021 |
| Investigating the effects of noise-estimation errors in simulated cochlear implant speech intelligibility AA Kressner, T May, RMT Høegh, KA Juhl, T Bentsen, T Dau Proceedings of the International Symposium on Auditory and Audiological …, 2017 | 2 | 2017 |
| Spatio-temporal neural distance fields for conditional generative modeling of the heart K Sørensen, P Diez, J Margeta, Y El Youssef, M Pham, JJ Pedersen, ... International Conference on Medical Image Computing and Computer-Assisted …, 2024 | | 2024 |
| EyeLoveGAN: Exploiting domain-shifts to boost network learning with cycleGANs JV Sundgaard, KA Juhl, JM Slipsager arXiv preprint arXiv:2203.05344, 2022 | | 2022 |
