Kildehenvisninger
[1] Smistad, E. et al. in ‘Annotation Web - An open-source web-based annotation tool for ultrasound images’ (2021)
[2] Støverud, K.-H. et al. ‘AeroPath: An airway segmentation benchmark dataset with challenging pathology and baseline method’ PLOS ONE 19, (2024)
[3] Fermann, B. S. et al. ‘Cardiac Valve Event Timing in Echocardiography Using Deep Learning and Triplane Recordings’ IEEE Journal of Biomedical and Health Informatics 28, (2024)
[4] Nyberg, J. et al. ‘Deep learning improves test–retest reproducibility of regional strain in echocardiography’ European Heart Journal - Imaging Methods and Practice 2, (2024)
[5] Holden Helland, R. et al. in ‘Glioblastoma Segmentation from Early Post-operative MRI: Challenges and Clinical Impact’ Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 (eds. Linguraru, M. G. et al.) (2024)
[6] ‘Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generation | PLOS One’
[7] Bouget, D. et al. ‘Raidionics: an open software for pre- and postoperative central nervous system tumor segmentation and standardized reporting’ Sci Rep 13, (2023)
[8] Vyver, G. V. D. et al. ‘Regional Image Quality Scoring for 2-D Echocardiography Using Deep Learning’ Ultrasound in Medicine & Biology 51, (2025)