Echonous, Inc.

Matthew Cook

Babajide Ayinde

Fan Zhang

Allen Lu

Eric Wong

Niko Pagoulatos

Dave Willis

Pavlos Moustakidis

Timothy Crossley

Alexandra Clements

Vasileios Sachpekidis

Systems and methods for automated recording of an ultrasound clip are based on quality scores of ultrasound images in a sequence of ultrasound image frames. An ultrasound imaging system includes a probe for capturing ultrasound images, an image buffer to store a sequence of image frames, a quality buffer to store a sequence of quality scores, and a computing subsystem that automatically records an ultrasound clip when the quality scores in the quality buffer corresponding to a set of contiguous image frames in the image buffer equal or exceed a first quality threshold and the set of contiguous image frames is at least a first predetermined size. Additionally, a smart capture feature automatically records an ultrasound clip including an alternate set of contiguous image frames having quality scores equaling or exceeding a second quality threshold that is less than the first quality threshold and meets a second predetermined size.

Systems and methods for automated ultrasound image recording based on quality scores

A facility for automatically establishing measurement location controls for Doppler ultrasound studies is described. The facility receives a first ultrasound image, and user input selecting an anatomical structure appearing in it. The facility performs localization to determine the location of the selected anatomical structure in the initial image, and determines a first placement of measurement location controls relative to the structure. On the ultrasound machine, the facility invokes one or more first Doppler ultrasound modes using the first placement. The facility receives a second ultrasound image produced by the ultrasound machine using the one or more first modes; determines a flow location and direction based on the second ultrasound image; and determines a second placement relative to the flow location. The facility invokes one or more second Doppler ultrasound modes using the second placement, and receives results from the invocation of the one or more second Doppler ultrasound modes.

Automatically establishing measurement location controls for doppler ultrasound

A facility for assessing an ultrasound image captured from a patient with a particular depth setting is described. The facility subjects the received ultrasound image to at least one neural network to produce, for each neural network, an inference. On the basis of the produced inferences, the facility determines whether the depth setting at which the ultrasound image was captured was optimal.

Automatic depth selection for ultrasound imaging

A facility for processing a medical imaging image is described. The facility applies to the image a first machine learning model trained to recognize a view to which an image corresponds, and a second machine learning model trained to identify any of a set of anatomical features visualized in an image. The facility accesses a list of permitted anatomical features for images corresponding to the recognized view, and filters the identified anatomical features to exclude any not on the accessed list. The facility causes the accessed image to be displayed, overlaid with a visual indication of each of the filtered identified anatomical features.

Automatically identifying anatomical structures in medical images in a manner that is sensitive to the particular view in which each image is captured

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Woodinville, WA, United States of America

Matthew Cook