Kardiolytics, subsidiary of Medicalgorithmics corporate group, was granted a patent (US 11521322 B2) for machine learning based segmentation of contrast filled coronary artery vessels on medical images.[/vc_column_text][vc_column_text]Innovation disclosed in the patent relate to machine learning based detection of vascular structures (coronary vessels) in CT angiography images. Automatic detection and segmentation of contrast filled coronary arteries in the images facilitate the diagnosis, treatment, and monitoring of coronary artery diseases.
The patented method for autonomous segmentation method comprises receiving an CT angiography scan, preprocessing the scan, and performing autonomous coronary vessels segmentation with the use of trained convolutional neural network (CNN).
All of the above make the unique, innovative Kardiolytics’ system – VCAST (Virtual Cardiac Stress Test), helping diagnose plaque buildups narrowing the coronary arteries as early as possible. VCAST is a true game changer in the cardiology world, bringing new, easy-to-perform, non-invasive and inexpensive tests available to a vast group of cardiology patients.
This is the next patent obtained by Kardiolytics. Securing patents for innovations and technologies will enable Kardiolytics to promote and commercialize inventions. Also, what is of the greatest importance – it will help protect Kardiolytics’ unique intellectual property to enable further development of the solution and improve CAD diagnostics (Coronary Artery Disease – the most common heart disease in the US).
Kardiolytics, a company creating solutions for medicine based on artificial intelligence, joined the Medicalgorithmics capital group in November 2022. The solutions developed by both companies are complementary and constitute a major step in the development of diagnostics of cardiac patients.
The global CT-FFR market is expected to reach USD 1,275 million by 2026, growing at a CAGR of 15.5% during the next decade. Factors driving the market include the increasing incidence of coronary artery disease, an aging patient population and advancements in CT technology.