Abstract: There is proposed a mechanism for determining whether or not an imaging probe, such as an ultrasound imaging probe, is at a desired orientation and/or position with respect to an anatomical structure. Image data of the imaging probe is processed to generate a 3D landmark model that contains anatomical landmarks of the anatomical structure. The 3D landmark model is then processed to determine whether or not the imaging probe is at the desired orientation and/or position.

Abstract: The present disclosure describes imaging systems configured to generate adaptive scanning protocols based on anatomical features and conditions identified during a prenatal scan of an object. Systems may include an ultrasound transducer configured to acquire echo signals responsive to ultrasound pulses transmitted toward a target region. Processors coupled with the transducer can generate an image frame from the echoes and provide the image frame to a first neural network. The first neural network may be configured to identify an anatomical feature in the image frame. An indication of the anatomical feature may be provided a second neural network. The second neural network may then determine an anatomical measurement to be obtained based, in part, on the feature identified. The processors may be further configured to cause an indicator of the anatomical measurement to be obtained to be displayed on a user interface.

Abstract: The present disclosure describes imaging systems configured to generate index information to indicate which image frames in a plurality of image frames include one or more target anatomical features, such as a head or femur of a fetus. The confidence levels of the presence of the target anatomical features are also determined. The system may be configured to determine if the target anatomical feature is present in an image frame by implementing at least one neural network. Merit levels based on the quality of the image frames may also be determined. Measurements of the one or more items of interest may be acquired. Visual representations (500) of the index information (502), confidence levels, merit levels, and/or measurements may be provided via a user interface. A user interface may receive user inputs based on the visual representations to navigate to specific image frames (508) of the plurality of image frames.

Abstract: The present disclosure describes imaging systems configured to generate adaptive scanning protocols based on anatomical features and conditions identified during a prenatal scan of an object. Systems may include an ultrasound transducer configured to acquire echo signals responsive to ultrasound pulses transmitted toward a target region. Processors coupled with the transducer can generate an image frame from the echoes and provide the image frame to a first neural network. The first neural network may be configured to identify an anatomical feature in the image frame. An indication of the anatomical feature may be provided a second neural network. The second neural network may then determine an anatomical measurement to be obtained based, in part, on the feature identified. The processors may be further configured to cause an indicator of the anatomical measurement to be obtained to be displayed on a user interface.

Abstract: A method for using an ultrasound imaging system including a disinfection system is disclosed. The disinfection system may include one or more ultraviolet light sources. The UV light sources may be included in a display. The disinfection system may be configured to operate when the display is parallel to a control panel of the ultrasound imaging system. The disinfection system may provide indications of the disinfection status of the ultrasound imaging system.

Abstract: An ultrasound imaging system may include a user interface that may be adapted based, at least in part, on usage data of one or more users. The functions of soft or hard controls may be changed in some examples. The layout or appearance of soft or hard controls may be altered in some examples. In some examples, seldom used controls may be removed from the user interface. In some examples, the user interface may be adapted based on an anatomical feature being imaged. In some examples, the usage data may be analyzed by an artificial intelligence/machine learning model, which may provide outputs that may be used to adapt the user interface.

Abstract: The invention provides a method for deriving a biometric parameter of a fetal heart. The method includes acquiring a plurality of ultrasound images of a region of interest, wherein the region of interest comprises a fetal heart and comparing the plurality of ultrasound images to a predefined clinical view. A group of ultrasound images related to the predefined clinical view are selected based on the comparison, wherein the group of ultrasound images represents at least one cardiac cycle. An anatomical landmark of the fetal heart is detected within an ultrasound image of the group of ultrasound images and the anatomical landmark of the fetal heart is detected or tracked across the group of ultrasound images. A biometric parameter of the fetal heart is then determined based on the detected or tracked anatomical landmark from one or more ultrasound images of the group of ultrasound images.

Abstract: An ultrasound imaging system may include a view recognition processor. The view recognition processor may determine when a specific view has been acquired by the ultrasound imaging system. A signal indicating the specific view has been acquired may be provided to an optimization state controller included in the ultrasound imaging system. Based on the signal, the optimization state controller may determine imaging settings optimized for the specific view. The optimized imaging settings may be provided to other components of the ultrasound imaging system to acquire or process the ultrasound image of the specific view with the optimized imaging settings.

Abstract: An ultrasound system according to some embodiments may include an ultrasound transducer configured to transmit ultrasound pulses toward tissue and generate echo signals responsive to the ultrasound pulses, a channel memory configured to store the echo signals, a beamformer configured to generated beamformed signals responsive to the echo signals, a neural network configured to receive one or more samples of the echo signals or the beamformed signals and produce a first type of ultrasound imaging data, and a processor configured to generate a second type of ultrasound imaging data, wherein the one or more processors may be further configured to generate an ultrasound image based on the first type of ultrasound imaging data and the second type of ultrasound imaging data and to cause a display communicatively coupled therewith to display the ultrasound image.

Abstract: The present disclosure describes imaging systems configured to generate volumetric images of a target feature based on anatomical landmarks identified during an ultrasound scan and in accordance with a user-selected view. Systems can include an ultrasound transducer configured to acquire echo signals responsive to ultrasound pulses transmitted toward a target region. A processor coupled with the transducer may present illustrative volumetric images of the target feature, each image corresponding to a particular view, for a user to select. The processor can then identify anatomical landmarks corresponding to the target feature embodied within 2D image frames, and based on the identified landmarks and user-selected view, provide instructions for manipulating the transducer to a target local to generate a 2D image frame specific to the view. Echo signals are then acquired at the target locale and used to generate an actual volumetric image of the target feature corresponding to the user-selected view.

Abstract: An ultrasound imaging system according to the present disclosure may include or be operatively associated with an ultrasound transducer configured to acquire echo signals responsive to ultrasound pulses transmitted toward a medium. The system may include a channel memory configured to store the acquired echo signals, a neural network coupled to the channel memory and configured to receive one or more samples of the acquired echo signals, one or more samples of beamformed signals based on the acquired echo signals, or both, and to provide imaging data based on the one or more samples of the acquired echo signals, the one or more samples of beamformed signals, or both, and may further include a display processor configured to generate an ultrasound image using the imaging data provided by the neural network. The system may further include a user interface configured to display the ultrasound image produced by the display processor.

Abstract: An ultrasound system according to some embodiments may include an ultrasound transducer configured to transmit ultrasound pulses toward tissue and generate echo signals responsive to the ultrasound pulses, a channel memory configured to store the echo signals, a beamformer configured to generated beamformed signals responsive to the echo signals, a neural network configured to receive one or more samples of the echo signals or the beamformed signals and produce a first type of ultrasound imaging data, and a processor configured to generate a second type of ultrasound imaging data, wherein the one or more processors may be further configured to generate an ultrasound image based on the first type of ultrasound imaging data and the second type of ultrasound imaging data and to cause a display communicatively coupled therewith to display the ultrasound image.

Abstract: The present disclosure describes imaging systems configured to generate index information to indicate which image frames in a plurality of image frames include one or more target anatomical features, such as a head or femur of a fetus. The confidence levels of the presence of the target anatomical features are also determined. The system may be configured to determine if the target anatomical feature is present in an image frame by implementing at least one neural network. Merit levels based on the quality of the image frames may also be determined. Measurements of the one or more items of interest may be acquired. Visual representations (500) of the index information (502), confidence levels, merit levels, and/or measurements may be provided via a user interface. A user interface may receive user inputs based on the visual representations to navigate to specific image frames (508) of the plurality of image frames.

Abstract: An ultrasound system with a deep learning neural network feature is used to eliminate haze artifacts in B mode images of the carotid artery by analysis of orthogonal information. In a described implementation the orthogonal information comprises the structural information of a B mode image and motion information of the same field of view as that of the B mode image. In another embodiment the neural network reduces haze artifacts by reducing TGC gain at the depth of artifacts.

Abstract: A medical imaging system configured to link acquired images to markers or tags on an anatomical illustration, based, at least in part on spatial and anatomical data associated with the acquired image. The medical imaging system may be further configured to generate a diagnostic report including the anatomical illustration containing the markers. The diagnostic report may allow a user to select a marker to view information associated with an acquired image and/or the acquired image. Multiple images may be associated with a marker, and/or multiple markers may be associated with an image. A set of 2D and/or 3D anatomical illustrations may be generated which contains markers from multiple diagnostic reports and updated automatically for an individual patient's anatomical model by the application to reflect measurements and/quantitative findings related to organ, tissue, and vessel size, location, deformation, and/or obstruction.

Abstract: A method for using an ultrasound imaging system including a disinfection system is disclosed. The disinfection system may include one or more ultraviolet light sources. The UV light sources may be included in a display. The disinfection system may be configured to operate when the display is parallel to a control panel of the ultrasound imaging system. The disinfection system may provide indications of the disinfection status of the ultrasound imaging system.

Abstract: The present disclosure describes imaging systems configured to generate adaptive scanning protocols based on anatomical features and conditions identified during a prenatal scan of an object. Systems may include an ultrasound transducer configured to acquire echo signals responsive to ultrasound pulses transmitted toward a target region. Processors coupled with the transducer can generate an image frame from the echoes and provide the image frame to a first neural network. The first neural network may be configured to identify an anatomical feature in the image frame. An indication of the anatomical feature may be provided a second neural network. The second neural network may then determine an anatomical measurement to be obtained based, in part, on the feature identified. The processors may be further configured to cause an indicator of the anatomical measurement to be obtained to be displayed on a user interface.

Abstract: An ultrasound imaging system (100) including a disinfection system is disclosed. The disinfection system may include one or more ultraviolet light sources (115). The UV light sources may be included in a display (105). The disinfection system may be configured to operate when the display is parallel to a control panel (120) of the ultrasound imaging system. The disinfection system may provide indications of the disinfection status of the ultrasound imaging system.

Abstract: An ultrasound system with a deep learning neural network feature is used to eliminate haze artifacts in B mode images of the carotid artery by analysis of orthogonal information. In a described implementation the orthogonal information comprises the structural information of a B mode image and motion information of the same field of view as that of the B mode image. In another embodiment the neural network reduces haze artifacts by reducing TGC gain at the depth of artifacts.

Abstract: An ultrasound system according to some embodiments may include an ultrasound transducer configured to transmit ultrasound pulses toward tissue and generate echo signals responsive to the ultrasound pulses, a channel memory configured to store the echo signals, a beamformer configured to generated beamformed signals responsive to the echo signals, a neural network configured to receive one or more samples of the echo signals or the beamformed signals and produce a first type of ultrasound imaging data, and a processor configured to generate a second type of ultrasound imaging data, wherein the one or more processors may be further configured to generate an ultrasound image based on the first type of ultrasound imaging data and the second type of ultrasound imaging data and to cause a display communicatively coupled therewith to display the ultrasound image.