公开(公告)号：US20230351593A1

公开(公告)日：2023-11-02

申请号：US18316010

申请日：2023-05-11

Applicant: EKO.AI PTE. LTD.

Inventor： James Otis HARE, II ,  Su Ping Carolyn LAM ,  Yoran HUMMEL ,  Matthew FROST ,  Mathias IVERSEN ,  Cyril EQUILBEC ,  Zhubo JIANG

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/90 ,  G06V20/40 ,  G06V10/764 ,  G06V10/82 ,  G16H30/40 ,  G16H70/20

CPC classification number: G06T7/0012 ,  G06T7/11 ,  G06T7/90 ,  G06V20/49 ,  G06V10/764 ,  G06V10/82 ,  G16H30/40 ,  G16H70/20 ,  G06T2207/30048 ,  G06T2207/10016 ,  G06V2201/031 ,  G06T2207/20084 ,  G06T2207/20081 ,  G06T2207/10132 ,  G06T2207/30101

Abstract: 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.