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Cardiovascular Imaging And Ai-Enabled Cardiac Image Processing
Benefit from state-of-the art custom software solutions and the power of AI to fight heart disease. We’ll assist you in research and software development.
- Our models for automatic segmentation of coronary arteries reconstruct the coronary artery tree with an accuracy of more than 90% (Sørensen-Dice coefficient of about 0.9).
- Accurate segmentation of the cardiovascular area allows the creation of a personalized treatment plan for each patient, taking into account their unique anatomy and tumor location. This enables delivery of a more precise and effective treatment while minimizing damage to surrounding healthy tissue.
- Our algorithms have also found application in cardiology. In the case of cardiovascular lesions, accurate image segmentation enables more effective diagnosis and treatment planning.
- Creating technology for the automatic coronary artery segmentation was one of the biggest challenges. Due to several factors, for instance: the complicated shape of coronary arteries; patient variability in terms of coronary arteries, particularly in cases of anomalies.
- Despite this difficulty, we have developed a technique for creating artificial intelligence algorithms for precise coronary artery segmentation.
Driving innovation across cardiology
At Graylight Imaging we bring expertise in both technology and medicine to create custom cutting-edge image analysis software for cardiology. We have successfully handled a number of cardiac projects and powered cardiological applications with state-of-the-art solutions.
AI in cardiac
AI algorithms are a great way to improve medical decision-making and diagnostic abilities through automated cardiac image analysis. You can advance your pathway from AI-enabled image reconstruction to segmentation and precise, patient-specific measurement in various cardiac imaging modalities.
Post processing technology for cardiac imaging
Discover advanced post-processing techniques and tools and dive into the myriad of data embedded in cardiovascular images. AI-enabled cardiac image processing can transform patient care at every stage of the imaging chain. Machine learning and Deep learning methods offer the extraction of new, clinically relevant information for patient and risk assessment.
- Tools for non-invasive assessment of cardiovascular conditions may benefit from the newest technology and cardiovascular imaging analysis.
- Advanced techniques and analysis solutions for cardiovascular imaging might be applied for interventional cardiology purposes as well.
- In interventional cardiology, artificial intelligence and biofluid simulation methods have shown the potential in providing data interpretation and automated analysis, as you may see in the graphic.
- During the project, based on the CT scans we provided a fully automated, patient-specific blood flow simulation before and after the stenting procedure.