Project description DEENESFRITPL Development of AI-assisted analysis of heart ultrasound images Heart ultrasound is an accessible, widely used, and cost-effective heart imaging method. However, interpretation of the acquired images requires advanced skills and is error-prone and vulnerable to inconsistencies. Funded by the European Innovation Council, the AI-driven cardiac ultrasound analysis project aims to automate the whole process of heart ultrasound analysis using AI-driven technology. The developed approach will seamlessly integrate with existing infrastructure in hospitals, enabling images and results to load onto hospital networks. The introduction of this new technology will dramatically enhance the quality of analysis, as well as allow for earlier diagnosis, better risk stratification and patient management. Show the project objective Hide the project objective Objective 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. Fields of science natural sciencesphysical sciencesacousticsultrasoundnatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Keywords Cardiac and Cardiovascular systems AI-driven tool Risk stratification Increased accessibility Echocardiography Early diagnosis Automation Deep neural networks Programme(s) HORIZON.3.1 - The European Innovation Council (EIC) Main Programme HORIZON.3.1.2 - The Accelerator Topic(s) HORIZON-EIC-2021-ACCELERATORCHALLENGES-01-01 - Strategic Digital and Health Technologies Call for proposal HORIZON-EIC-2021-ACCELERATORCHALLENGES-01 See other projects for this call Funding Scheme HORIZON-EIC-ACC-BF - HORIZON EIC Accelerator Blended Finance Coordinator LIGENCE UAB Net EU contribution € 2 500 000,00 Address TAIKOS PR. 54 LT-51305 KAUNAS Lithuania See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region Lietuva Vidurio ir vakarų Lietuvos regionas Kauno apskritis Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 3 574 343,75
