Eko.ai Pte. Ltd.

Cyril Equilbec

Su Ping Carolyn Lam

James Otis Hare, Ii

Mathias Iversen

Zhubo Jiang

Yoran Hummel

Matthew Frost

A computer-implemented method for grading of Aortic Stenosis severity performed by an automated workflow engine executed by at least one processor includes receiving, from a memory, a plurality of echocardiogram images a heart. The plurality of echocardiogram (echo) images according to 2D images and Doppler modality images. The 2D images are classified by view type, and the Doppler modality images are classified by region. The regions of interest in the 2D images are segmented to produce segmented 2D images. The Doppler modality images are segmented to generate waveform traces to produce segmented Doppler modality images. The segmented images are used to calculate measurements of cardiac features of the heart. A conclusion of Aortic Stenosis severity is generated by comparing the calculated measurements to cardiac guidelines. A report is then output showing the calculated measurements of the cardiac features that fall within or outside of the cardiac guidelines.

Automatic clinical workflow that recognizes and analyzes 2D and doppler modality echocardiogram images for automated cardiac measurements and grading of aortic stenosis severity

Growing community of inventors

Singapore, Singapore

Cyril Equilbec