Publikasjoner
- Toward Robust Cardiac Segmentation Using Graph Convolutional Networks
- Real-time guidance by deep learning of experienced operators to improve the standardization of echocardiographic acquisitions
- Automatic measurements of left ventricular volumes and ejection fraction by artificial intelligence: clinical validation in real time and large databases Les publikasjonen
- Real-time guiding by deep learning during echocardiography to reduce left ventricular foreshortening and measurement variability
- Noninvasive intracranial pressure assessment by optic nerve sheath diameter: Automated measurements as an alternative to clinician-performed measurements Les publikasjonen
- Left-Ventricular Volume Estimation in Contrast-Enhanced Echocardiography Using Deep Learning
- Automated 2-D and 3-D Left Atrial Volume Measurements Using Deep Learning
- Deep Learning for Improved Precision and Reproducibility of Left Ventricular Strain in Echocardiography: A Test-Retest Study Les publikasjonen
- Segmentation of 2D cardiac ultrasound with deep learning: simpler models for a simple task
- Real-Time Echocardiography Guidance for Optimized Apical Standard Views Les publikasjonen
Annen formidling
- Real-time segmentation of the aorta in 2D ultrasound images for detecting abdominal aorta aneurism - abstract
- Response to “Minimal Detectable Change and Reproducibility of Echocardiographic Strain: Implications for Clinical Practice”
- Deep learning in real-time ultrasound and digital pathology - From annotation and training to real-world application
- Machine learning in Echocardiography
- EchoBot: An open-source robotic ultrasound system
- EchoBot: An open-source robotic ultrasound system
- Centrelines and airways extraction from lung CT for navigated bronchoscopy: a comparison of three methods
