| Deep metric learning for otitis media classification JV Sundgaard, J Harte, P Bray, S Laugesen, Y Kamide, C Tanaka, ... Medical Image Analysis 71, 102034, 2021 | 52 | 2021 |
| A deep learning approach for detecting otitis media from wideband tympanometry measurements JV Sundgaard, P Bray, S Laugesen, J Harte, Y Kamide, C Tanaka, ... IEEE Journal of Biomedical and Health Informatics, 2022 | 12 | 2022 |
| Inter-rater reliability of the diagnosis of otitis media based on otoscopic images and wideband tympanometry measurements JV Sundgaard, M Värendh, F Nordström, Y Kamide, C Tanaka, J Harte, ... International Journal of Pediatric Otorhinolaryngology 153, 111034, 2022 | 7 | 2022 |
| Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection P López Diez, JV Sundgaard, F Patou, J Margeta, 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 | 5 | 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 |
| Was that so Hard? Estimating Human Classification Difficulty MR Hannemose, JV Sundgaard, NK Ternov, RR Paulsen, ... Applications of Medical Artificial Intelligence: First International …, 2022 | 3 | 2022 |
| Multi-modal data generation with a deep metric variational autoencoder JV Sundgaard, MR Hannemose, S Laugesen, P Bray, J Harte, Y Kamide, ... Proceedings of the Northern Lights Deep Learning Workshop 2023 4, 2023 | 1 | 2023 |
| Multi‐modal deep learning for joint prediction of otitis media and diagnostic difficulty JV Sundgaard, MR Hannemose, S Laugesen, P Bray, J Harte, Y Kamide, ... Laryngoscope Investigative Otolaryngology, 2024 | | 2024 |
| Deep reinforcement learning and convolutional autoencoders for anomaly detection of congenital inner ear malformations in clinical CT images PL Diez, JV Sundgaard, J Margeta, K Diab, F Patou, RR Paulsen Computerized Medical Imaging and Graphics, 102343, 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 |
| Deep learning methods for pediatric middle ear diagnostics JV Sundgaard Technical University of Denmark, 2022 | | 2022 |
| Multimodal deep transfer learning for the analysis of optical coherence tomography scans and retinal fundus photographs Z Tsangalidou, E Fong, JV Sundgaard, TJ Abrahamsen, K Kvist NeurIPS 2022 Workshop on Learning Meaningful Representations of Life, 2022 | | 2022 |
| Evaluation of respiratory motion correction in PET/CT using a 3D printed phantom JH Vilsbøll, HSW Hasler, LDL Duchstein, JE Wilhjelm, MN Lonsdale 30th Annual Congress of the European Association of Nuclear Medicine, 2017 | | 2017 |
Rasmus R. PaulsenProfessor in Medical Image Analysis, DTU Compute, Technical University of DenmarkVerified email at dtu.dk
