Caption Health, Inc.

Siemens Medical Solutions Usa, Inc.

Other

Bay Labs, Inc.

Ecton Inc.

Penrith Corporation

Michael G Cannon

Nicolas Poilvert

Kilian Koepsell

Charles Cadieu

Ha Hong

Joseph A Urbano

Johan Mathe

Natalia Bilenko

Nathanael Romano

Kevin S Randall

Charles Chen

Nina Miolane

Anthony P Lannutti

Jodi Schwartz Klessel

Andrew J Wood

Raymond F Weymer, Jr

Lawrence A Engle

Nripesh Parajuli

Ian Balmain Hewitt

Ali Chaudhry

Richard K Pallo

Bryon L Thompson

Dorin Comaniciu

Xiang Sean Zhou

Sriram Krishnan

George D'Angelo

George C Ku

Samuel Surette

Ching Hsieh

Charles Frye

Michael J Filippone, Jr

Allen Dutton

Susan McGuire

Provided herein are platforms, systems, and methods for providing ultrasound imaging guidance for automatic evaluation of image quality over a plurality of sub-views.

Systems and methods for volume-based ultrasound guidance and image analysis

An ultrasound guidance dynamic progression method includes selecting a predetermined ultrasound diagnostic workflow in memory of an ultrasound diagnostic computing system, the workflow including a sequence of views of a target organ. The method further includes selecting a first view in the sequence and presenting guidance in a display of the computing system for the first view, for instance visual, audible or haptic feedback. The method yet further includes acquiring imagery in the computing system in association with the first view, and detecting an anomalous feature of the acquired imagery. Finally, the method includes selecting a different view in the sequence as a substitute for a next one of the views in the sequence in response to having detected the anomalous feature, and further presenting different guidance in the display for the different view in lieu of guidance for the next one of the views.

Mid-procedure view change for ultrasound diagnostics

Embodiments of the present invention provide a method, system and computer program product for ultrasound image acquisition optimization according to different respiration modes. A method for ultrasound image acquisition optimization according to different respiration modes includes acquiring by an ultrasound imaging device, an ultrasound image of a target organ. The method further includes comparing attributes of the acquired ultrasound image to association data in a data store of associations associating attributes of previously acquired ultrasound imagery of different images of the target organ with different modes of respiration. Finally, the method includes determining from the comparison, a mode of respiration evident from the acquired ultrasound image and presenting the determined mode in the ultrasound imaging device.

Ultrasound image acquisition optimization according to different respiration modes

A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Video clip selector for medical imaging and diagnosis

A saliency mapping method includes displaying video clip imagery of an organ in a display of a computer and submitting the imagery to a neural network trained to produce a probability of an existence of a physical feature of the organ. In response, the probability is received along with a pixel-wise mapping of dispositive pixels in the imagery resulting in the probability. Variations of the imagery are then repeatedly resubmitted to the neural network, each including a change to one or more of the pixels in the imagery. Thereafter, for each resubmission, a change is measured in the probability and then correlated to the changed pixels. Finally, a graphical indicator is overlain on the display of the imagery corresponding to each of the pixels determined through the repeated resubmission to be dispositive based upon a threshold measured change in probability.

Saliency mapping of imagery during artificially intelligent image classification

Embodiments of the present invention provide a method, system and computer program product for video clip quality determination in medical device imaging and diagnosis. In an embodiment of the invention, a method for video clip quality determination in medical imaging includes first retrieving from a data store into memory of a host computer, video clip imagery of a target organ. Then, a quality value assigned to the video clip imagery may be identified in connection with the retrieved video clip imagery. A measurement of the target organ is computed based upon the retrieved video clip imagery. Finally, a confidence in respect to the computed measurement is determined based upon the identified quality value and the confidence determination displayed in a user interface provided by the host computer.

Confidence determination in a medical imaging video clip measurement based upon video clip image quality

Embodiments of the invention provide a method, system and computer program product for artificially intelligent ejection fraction determination. In a method for artificially intelligent ejection fraction determination, a neural network is loaded into memory of a computer, that has been trained with different sets of cardiac imaging data acquired during imaging of a ventricle for different hearts and a known ejection fraction for each of the sets. Then, a contemporaneous set of imaging data is acquired of a ventricle of a heart and the contemporaneous set of imaging data is provided to the neural network. Finally, an ejection fraction determination output by the neural network is displayed in a display of the computer without tracing a ventricle boundary of the heart.

Artificially intelligent ejection fraction determination

Embodiments contemplate methods and systems for determining an image performance measurement in an ultrasound system. Embodiments contemplate that data may be received from a remote unit of an ultrasound imaging system. One or more determinations of the measure of performance of an image may be made, where the image may be derivable from at least part of the data. The measure of image performance may be displayed on a main unit of the ultrasound imaging system.

Ultrasound image performance determination

The disclosed embodiments include a method, system, and device for conducting ultrasound interrogation of a medium. The method includes transmitting a non-beamformed or beamformed ultrasound wave into the medium, receiving more than one echoed ultrasound wave from the medium, and converting the received echoed ultrasound wave into digital data. The method may further transmit the digital data. The transmission may be wireless. The system may include a main unit, a remote unit, a locator module, transducer elements, an analog-to-digital converter in communication with the transducer elements, and a transmitter in communication with the analog-to-digital converter. The main unit and the remote unit may be part of an ultrasound imaging system and the remote unit may communicate with the main unit. The locator module may communicate with the remote unit or the main unit. The locator module may identify a location of the remote unit or the main unit.

Transducer array imaging system

The embodiments contemplate systems and methods for detecting moving tissue within an object. In one such method, a first and second ultrasound pulse are transmitted at a first sample volume within an object. A first echo signal of the first ultrasound pulse is received from the first sample volume and a second echo signal of the second ultrasound pulse is received from the first sample volume. An estimate of position displacement data of the first sample volume is computed from the first and second echo signals, and the estimate of position displacement data is compared to a predetermined position displacement data threshold indicative of moving tissue. A determination is made, based on the comparison, whether the first sample volume corresponds to moving tissue and, based on the determination, the transmitting, receiving, computing and determining is repeated for a second sample volume.

Automated movement detection with audio and visual information

The embodiments contemplate methods and devices for communicating an acoustic emission via an array of transducers and wirelessly communicating data via a transceiver, where the transceiver may be in communication with the array of transducers. Embodiments also contemplate providing power for the acoustic emission via a power source and providing information regarding a temperature sensor to the transceiver. The wirelessly communicated data may include the information regarding the temperature sensor. Embodiments also contemplate processing the wirelessly communicated data at a relatively remote location with respect to both the power source and the temperature sensor.

Growing community of inventors

Haverford, PA, United States of America

Michael G Cannon