Forschungsteam vor Bildschirmen mit Visualisierungen künstlicher neuronaler Netze

Projekt

AI-driven cardiac ultrasound analysis

Heart ultrasound is the most versatile, most widely used, and cost-effective heart imaging method. Accessibility to ultrasound imaging is growing rapidly as the devices are getting cheaper and smaller. However, interpretation of the acquired images creates a bottleneck; it requires substantial skill, it is long, manua…

Heart ultrasound is the most versatile, most widely used, and cost-effective heart imaging method. Accessibility to ultrasound imaging is growing rapidly as the devices are getting cheaper and smaller. However, interpretation of the acquired images creates a bottleneck; it requires

substantial skill, it is long, manual, and prone to errors and variability. Ligence is remodelling the quality, difficulty, and length of echocardiography with an AI-driven tool to automate the whole analysis of heart ultrasound images. Deep learning neural networks classify heart image

views, detect heart cycle phases, and perform measurements. It seamlessly integrates with existing infrastructure in hospitals, meaning that moments after images are loaded onto the hospital's network the results are accessible on any workstation. This results in dramatically increased

accessibility and analysis quality, earlier diagnosis, and better patient risk stratification, monitoring, and patient management.

Technologien

Förderungen