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 t...
ver más
¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video
Duración del proyecto: 28 meses
Fecha Inicio: 2022-09-14
Fecha Fin: 2025-01-31
Líder del proyecto
LIGENCE UAB
No se ha especificado una descripción o un objeto social para esta compañía.
Presupuesto del proyecto
4M€
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
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.