Abstract: Methods and systems are provided for automatically characterizing lesions in ultrasound images. In one example, a method includes automatically determining an A/B ratio of a region of interest (ROI) via an A/B ratio model that is trained to output the A/B ratio using a B-mode image of the ROI and an elastography image of the ROI as inputs, and displaying the A/B ratio on a display device.

Abstract: Various methods and systems are provided for ultrasound imaging. In one embodiment, a method comprises acquiring, via an ultrasound probe, Doppler measurements over a plurality of cardiac cycles, evaluating a flow profile comprising the Doppler measurements to detect an abnormality in the flow profile, and displaying, via a display device, the flow profile with a reference flow profile overlaid thereon. In this way, the attention of a physician evaluating results from an ultrasound imaging examination may be directed to abnormal flow that is potentially indicative of pathologies, thereby enabling earlier and more accurate diagnosis of pathologies.

Abstract: Various methods and systems are provided for automatically or semi-automatically adjusting one or more ultrasound imaging parameters for imaging in a second mode based on images obtained in a first mode. In one example, a method includes operating an ultrasound imaging system in a first operating mode, determining an anatomy imaged by the ultrasound imaging system in the first operating mode, and responsive to an operating mode transition request, adjusting imaging parameters of the ultrasound imaging system in a second operating mode based on the first operating mode and the anatomy imaged in the first operating mode.

Abstract: Various methods and systems are provided for transforming a style of an image into a different style while preserving content of the image. In one example, a method includes transforming a first image acquired via a medical imaging system into a second image based on visual characteristics of a third image using a system of deep neural networks configured to separate visual characteristics from content of an image, where the second image includes a content of the first image and the visual characteristics of the third image and the first and second images have different visual characteristics. The transformed second image may then be presented to a user.

Abstract: Various methods and systems are provided for ultrasound imaging. In one embodiment, a method comprises acquiring, via an ultrasound probe, Doppler measurements over a plurality of cardiac cycles, evaluating a flow profile comprising the Doppler measurements to detect an abnormality in the flow profile, and displaying, via a display device, the flow profile with a reference flow profile overlaid thereon. In this way, the attention of a physician evaluating results from an ultrasound imaging examination may be directed to abnormal flow that is potentially indicative of pathologies, thereby enabling earlier and more accurate diagnosis of pathologies.

Abstract: Methods and systems are provided for automatically characterizing contrast agent microbubbles in contrast-enhanced ultrasound images. In one example, a method includes generating, via a contrast bubble model, a density map of contrast agent microbubbles in a region of interest (ROI) of a contrast-enhanced ultrasound image and displaying the density map on a display device.

Abstract: Methods and systems are provided for automatically characterizing lesions in ultrasound images. In one example, a method includes automatically determining an A/B ratio of a region of interest (ROI) via an A/B ratio model that is trained to output the A/B ratio using a B-mode image of the ROI and an elastography image of the ROI as inputs, and displaying the A/B ratio on a display device.

Abstract: Various methods and systems are provided for automatically or semi-automatically adjusting one or more ultrasound imaging parameters for imaging in a second mode based on images obtained in a first mode. In one example, a method includes operating an ultrasound imaging system in a first operating mode, determining an anatomy imaged by the ultrasound imaging system in the first operating mode, and responsive to an operating mode transition request, adjusting imaging parameters of the ultrasound imaging system in a second operating mode based on the first operating mode and the anatomy imaged in the first operating mode.

Abstract: Systems and methods are provided for fully automated image optimization based on automated organ recognition. In medical imaging systems, during medical imaging based on a particular imaging technique, an anatomical feature in an area being imaged may be automatically identifying, and based on the identifying of the anatomical feature, one or more imaging parameters or settings for optimizing imaging quality for the identified anatomical feature may be automatically determined. Imaging functions may then be configured based on the determined one or more imaging parameters or settings, and, based on processing of medical imaging dataset acquired based on that configuration, one or more medical images for rendering. A deep learning and/or neural network based model may be used in identifying the anatomical feature and selecting the one or more imaging parameters or settings.

Abstract: Various methods and systems are provided for transforming a style of an image into a different style while preserving content of the image. In one example, a method includes transforming a first image acquired via a medical imaging system into a second image based on visual characteristics of a third image using a system of deep neural networks configured to separate visual characteristics from content of an image, where the second image includes a content of the first image and the visual characteristics of the third image and the first and second images have different visual characteristics. The transformed second image may then be presented to a user.

Abstract: Various methods and systems are provided for compensating for motion in medical images. As one example, a method for a medical imaging system may include independently tracking motion of a first object and motion of a second object across a plurality of image frames acquired with the medical imaging system, and for a selected image frame of the plurality of image frames, compensating the selected image frame for the motion of the first object and for the motion of the second object to generate a compensated selected image frame and outputting the compensated selected image frame for display on a display device, where the compensation for the motion of the first object is performed independently of the compensation for the motion of the second object.

Abstract: Systems and methods are provided for fully automated image optimization based on automated organ recognition. In medical imaging systems, during medical imaging based on a particular imaging technique, an anatomical feature in an area being imaged may be automatically identifying, and based on the identifying of the anatomical feature, one or more imaging parameters or settings for optimizing imaging quality for the identified anatomical feature may be automatically determined. Imaging functions may then be configured based on the determined one or more imaging parameters or settings, and, based on processing of medical imaging dataset acquired based on that configuration, one or more medical images for rendering. A deep learning and/or neural network based model may be used in identifying the anatomical feature and selecting the one or more imaging parameters or settings.

Abstract: Methods and systems for displaying ultrasound images are provided. The method provides receiving a user input selecting a shear-wave mode for an ultrasound probe and obtaining shear-wave data of a region of interest (ROI) acquired by the ultrasound probe when in the shear-wave mode. The method further includes receiving a user input selecting a strain mode for the ultrasound probe and obtaining strain data of the ROI acquired by the ultrasound probe when in the strain mode. The method also includes generating an image of the shear-wave data and an image of the strain data and receiving a user input to display the shear-wave image and the strain image. Further, the method provides displaying the shear-wave image and the strain image concurrently.

Abstract: Methods and systems for displaying ultrasound images are provided. The method provides receiving a user input selecting a shear-wave mode for an ultrasound probe and obtaining shear-wave data of a region of interest (ROI) acquired by the ultrasound probe when in the shear-wave mode. The method further includes receiving a user input selecting a strain mode for the ultrasound probe and obtaining strain data of the ROI acquired by the ultrasound probe when in the strain mode. The method also includes generating an image of the shear-wave data and an image of the strain data and receiving a user input to display the shear-wave image and the strain image. Further, the method provides displaying the shear-wave image and the strain image concurrently.