公开(公告)号：US11446009B2

公开(公告)日：2022-09-20

申请号：US17093365

申请日：2020-11-09

Applicant: Eko.AI Pte. Ltd.

Inventor： James Otis Hare, II ,  Paul James Seekings ,  Su Ping Carolyn Lam ,  Yoran Hummel ,  Jasper Tromp ,  Wouter Ouwerkerk ,  Zhubo Jiang

IPC: A61B8/08 ,  G06N3/08 ,  G16H30/20

Abstract: An automated workflow receives a patient study comprising cardiac biomarker measurements and a plurality of echocardiographic images taken by an ultrasound device of a patient heart. A filter separates the plurality of echocardiogram images by 2D images and Doppler modality images based on analyzing image metadata. The 2D images are classified by view type, and the Doppler modality images are classified by view type. The cardiac chambers are segmented in the 2D images, and the Doppler modality images are segmented to generate waveform traces, producing segmented 2D images and segmented Doppler modality images. Using both the sets of images, measurements of cardiac features for both left and right sides of the heart are calculated. The cardiac biomarker measurements and the calculated measurements are compared with international cardiac guidelines to generate conclusions, and a report is output showing the measurements that fall within or outside of the guidelines.

公开(公告)号：US11301996B2

公开(公告)日：2022-04-12

申请号：US16833001

申请日：2020-03-27

Applicant: EKO.AI PTE. LTD.

Inventor： James Otis Hare, II ,  Paul James Seekings ,  Su Ping Carolyn Lam ,  Yoran Hummel ,  Jasper Tromp ,  Wouter Ouwerkerk ,  Zhubo Jiang

IPC: G06T7/00 ,  G16H40/67 ,  G16H40/63 ,  G16H30/40 ,  G16H30/20 ,  G06T7/11 ,  G06N3/08 ,  G06N3/04

Abstract: A method for training neural networks of an automated workflow performed by a software component executing on a server in communication with remote computers at respective laboratories includes downloading and installing a client and a set of neural networks to a first remote computer of a first laboratory, the client accessing the echocardiogram image files of the first laboratory to train the set of neural networks and to upload a first trained set of neural networks to the server. The process continues until the client and the second trained set of neural networks is downloaded and installed to a last remote computer of a last laboratory, the client accessing the echocardiogram image files of the last laboratory to continue to train the second trained set of neural networks and to upload a final trained set of neural networks to the server.

公开(公告)号：US10702247B2

公开(公告)日：2020-07-07

申请号：US16707622

申请日：2019-12-09

Applicant: Eko.AI PTE. LTD.

Inventor： James Otis Hare, II ,  Paul James Seekings ,  Su Ping Carolyn Lam ,  Yoran Hummel ,  Jasper Tromp ,  Wouter Ouwekerk

IPC: A61B8/08 ,  A61B8/00 ,  G16H30/20 ,  G16H30/40 ,  A61B8/14 ,  G06T7/00 ,  A61B8/06

Abstract: An automated workflow performed by software executing on at least one processor includes receiving a plurality of echocardiogram images taken by an ultrasound device. A filter separates the plurality of echocardiogram images by 2D images and Doppler modality images based on analyzing image metadata. The 2D images are classified by view type, and the Doppler modality images are classified by view type. The cardiac chambers are segmented in the 2D images, and the Doppler modality images are segmented to generate waveform traces, producing segmented 2D images and segmented Doppler modality images. Using both the sets of images, measurements of cardiac features for both left and right sides of the heart are calculated. The calculated measurements are compared with international cardiac guidelines to generate conclusions and a report is output showing the calculated measurements that fall both within and outside of the guidelines.