Ge Precision Healthcare LLC

General Electric Company

Dani Pinkovich

Menachem Halmann

Cynthia A Owen

Antonio Fabian Fermoso

Alexander Sokulin

Carmit Shiran

Sarit Shwartz

Robert John Anderson

Noa Alkobi

Christian Fritz Perrey

Peter Lysyansky

Mor Vardi

Walter Duda, Jr

Alex Sokulin

Various methods and systems are provided for imaging a needle using an ultrasound imager. In one example, a method may include receiving a target path or a target area of a needle, and adjusting a steering angle of an ultrasound beam emitted from an ultrasound probe based on the target path or the target area.

Methods and systems for imaging a needle from ultrasound imaging data

Systems and methods are provided for ultrasound imaging with real-time feedback for cardiopulmonary resuscitation (CPR) compressions. Ultrasound images generated based on received echo ultrasound signals during cardiopulmonary resuscitation (CPR) of a patient may be processed, and based on the processing of the ultrasound images, real-time information relating to the cardiopulmonary resuscitation (CPR) may be determined. Feedback for assisting in conducting the cardiopulmonary resuscitation (CPR) may be generated based on the information. The feedback may include information and/or indications relating to compressions applied during the cardiopulmonary resuscitation (CPR). The feedback may be configured for outputting during displaying of the generated ultrasound images.

Ultrasound imaging with real-time visual feedback for cardiopulmonary resuscitation (CPR) compressions

Systems and methods are provided for enhanced heart medical imaging operations, particularly as by incorporating use of artificial intelligence (AI) based fetal heart functional analysis and/or real-time and automatic ejection fraction (EF) measurement and analysis.

Methods and systems for medical imaging based analysis of ejection fraction and fetal heart functions

Various methods and systems are provided for a medical imaging system. In one embodiment, a method includes acquiring a series of medical images of a lung, identifying a pleural line in each medical image of the series, evaluating the pleural line for irregularities in each medical image of the series, and outputting an annotated version of each medical image of the series, the annotated version including visual markers for healthy pleura and irregular pleura. In this way, an operator of the medical imaging system may be alerted to pleural irregularities during a scan.

Methods and systems for detecting pleural irregularities in medical images

A system and method for tracking an anatomical structure over time based on Pulsed-Wave (PW) Doppler signals of a Multi-Gated Doppler (MGD) signal is provided. The method may include identifying a gate corresponding with a selected anatomical structure. The method may include analyzing an MGD signal to track the selected anatomical structure over an extended period of time by selecting, at a plurality of sample times during the extended period of time, a PW Doppler signal from a plurality of PW Doppler signals of the MGD signal. Each of the selected PW Doppler corresponds with the selected anatomical structure at the particular sample time. The method may include presenting a continuous PW Doppler signal generated from each of the PW Doppler signals selected at each of the sample times during the extended period of time at a display system.

Method and system for tracking an anatomical structure over time based on pulsed-wave doppler signals of a multi-gated doppler signal

Methods and systems are provided for augmenting ultrasound image training data, which may be used to train one or more machine learning models. One example method for augmenting ultrasound training data comprises, selecting an ultrasound image and a ground truth output corresponding to the ultrasound image, determining a first modification to apply to the ultrasound image, applying the first modification to the ultrasound image to produce an augmented ultrasound image, modifying the ground truth output based on the first modification to produce an augmented ground truth output corresponding to the augmented ultrasound image, and training a machine learning model using the augmented ultrasound image and the augmented ground truth output. In this way, a machine learning model may learn a more robust mapping from ultrasound image features to expected output, with less probability of overfitting, and with increased generalizability to noisy ultrasound images, or ultrasound images containing artifacts.

Systems and methods for generating augmented training data for machine learning models

A system and method for simultaneously presenting Doppler signals of a Multi-Gated Doppler (MGD) signal corresponding to different anatomical structures is provided. The method includes receiving an MGD signal having a plurality of Doppler signals. The method includes analyzing the MGD signal to select multiple gates, each of the gates corresponding with a Doppler signal, and each of the selected gates associated with a different anatomical structure. The method includes selecting a set of parameters for each of the selected gates and applying each selected set of parameters for each of the selected gates. The selected set of parameters for each of the selected gates may be one or both of image acquisition parameters or display processing parameters. The method includes simultaneously presenting the Doppler signal for each of the selected gates at a display system after the each selected set of parameters is applied.

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Tirat Carmel, Israel

Dani Pinkovich