Eko.ai Pte. Ltd.

Andrie Ochtman

James Otis Hare, Ii

Su Ping Carolyn Lam

Yoran Hummel

Mathias Iversen

Artificial intelligence (AI)-based guidance for an ultrasound device to improve capture of echo image views comprises receiving a plurality of the echo images captured by a probe of the ultrasound device, the ultrasound device including a display and a user interface (UI) that displays the echo images to a user. One or more neural networks process the echo images to continuously attempt to automatically classify the echo images by view type and generates corresponding classification confidence scores. The view type of the echo images are simultaneously displayed in the UI along with the echo images. Feedback indications are displayed in the UI of the ultrasound device to the user, where the feedback indications include which directions to move the probe of the ultrasound device so the probe can be placed in a correct position to capture and successfully classify the echo images.

Artificial intelligence (AI)-based guidance for an ultrasound device to improve capture of echo image views

Artificial intelligence (AI) recognition of echocardiogram (echo) images by a mobile ultrasound device comprises receiving a plurality of the echo images captured by the ultrasound device, the ultrasound device including a display and a user interface (UI) that displays the echo images to a user, the echo images comprising 2D images and Doppler modality images of a heart. One or more neural networks process the echo images to automatically classify the echo images by view type. The view type of the echo images is simultaneously displayed in the UI of the ultrasound device along with the echo images. A report is generated showing the calculated measurements of features in the echo images. The report showing the calculated measurements is displayed on a display device.

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Singapore, Singapore

Andrie Ochtman