Abstract: An application running in a mobile device displays an ultrasound image obtained by a connected ultrasound scanner. A button is displayed on the device, which, when activated, automatically connects the device to a remote reviewer in a virtual videoconferencing room, without the operator of the scanner needing to input user credentials. Upon activating the button, or otherwise triggering the request for a review, pre-stored login credentials are automatically retrieved and used for connecting the operator to the room. The remote reviewer may be connected to the room upon accepting the request for review, without having to input user credentials, which are pre-stored and automatically retrieved.

Abstract: A plurality of ultrasound frames of a fetus are acquired using an ultrasound scanner, which may be oriented arbitrarily with respect to the fetus during the acquisition. The ultrasound frames are processed against an artificial intelligence model to predict a different cut line on each of the ultrasound frames. Each cut line is predicted to be exterior to an image of the fetus appearing on the ultrasound frame. The different cut lines on the plurality of ultrasound frames are then used to identify ultrasound data in the image frames to generate a 3D representation of the fetus.

Abstract: A method and system provide for the identification of a tendon in ultrasound imaging data, by deploying an artificial intelligence (AI) model to execute on a computing device, wherein the AI model is trained to identify a plurality of different types of tendons imaged in ultrasound imaging data, and when deployed, the computing device generates a probability for each of the plurality of different types of tendons that the type of tendon is imaged in new ultrasound imaging data and wherein such probability is corroborated by at least one live deployment input.

Abstract: The present embodiments relate generally to systems and methods for ultrasound imaging. The methods may involve: establishing a wireless network between an ultrasound imaging device and a display device; acquiring ultrasound image data using ultrasound acquisition parameters; transmitting the ultrasound image data from the ultrasound imaging device to the display device over the wireless network; receiving the ultrasound image data; measuring a quality of service parameter of the received ultrasound image data; determining whether the measured quality of service parameter is less than an expected quality of service parameter, the expected quality of service parameter being determined based on the ultrasound acquisition parameters used to acquire the ultrasound image data; and in response to determining that the measured quality of service parameter is less than the expected quality of service parameter, adjusting a network parameter of the wireless network to reduce network traffic on the wireless network.

Abstract: The present embodiments relate generally to systems and methods for acquiring raw ultrasound data from an ultrasound machine using a wirelessly connected device. The systems can be configured to display ultrasound images on a display device and receive input to select the ultrasound images for which to retrieve corresponding raw ultrasound data from the ultrasound machine. A raw data buffer provided at the ultrasound machine may be capable of storing a first time duration of raw ultrasound data. An image display buffer provided at the wireless device may store: processed ultrasound image data corresponding to the raw ultrasound data stored in the raw data buffer; and previously-received processed ultrasound image data that has no corresponding raw ultrasound data stored in the raw data buffer.

Abstract: During acquisition of an ultrasound image feed, ultrasound control data frames are acquired that may be interspersed amongst the ultrasound data frames. The control data frames may use consistent reference scan parameters, irrespective of the scanner settings, and may not need to be converted to image frames. The control data frames can be passed to an artificial intelligence model, which predicts the suitable settings for scanning the anatomy that is being scanned. The artificial intelligence model can be trained with a dataset containing different classes of ultrasound control data frames for different settings, where substantially all the ultrasound control data frames in the dataset are consistently acquired using the reference scan parameters.

Abstract: An ultrasound imaging system comprising a multi-use electronic display device and an ultrasound imaging device. The multi-use electronic display device is capable of communicating with one or more ultrasound imaging devices and selecting which to connect with based on at least one of previously store information, user input, and information gathered from the ultrasound imaging devices. The multi-use electronic display device may communicate with the ultrasound imaging devices while they are in a low power standby state. This approach reduces the complexity of the pairing process and provides a means for quickly and easily selecting between multiple ultrasound imaging devices.

Abstract: A method and system for assessing medical images for suitability in clinical interpretation is described herein. The method and system involve: acquiring a medical image; inputting the medical image into a machine learning model, wherein the machine learning model is configured to determine a quality value based on the medical image; determining whether the quality value meets a quality threshold associated with a target clinical application; and when the quality value meets the quality threshold associated with the target clinical application, permitting clinical interpretation of the medical image for the target clinical application.

Abstract: An application running in a mobile device displays an ultrasound image obtained by a connected ultrasound scanner. A button is displayed on the device, which, when activated, automatically connects the device to a remote reviewer in a virtual videoconferencing room, without the operator of the scanner needing to input user credentials. Upon activating the button, or otherwise triggering the request for a review, pre-stored login credentials are automatically retrieved and used for connecting the operator to the room. The remote reviewer may be connected to the room upon accepting the request for review, without having to input user credentials, which are pre-stored and automatically retrieved.

Abstract: Ultrasound images are adjusted according to the size of the display area available to display them, so that image detail is displayed with a large enough physical size to discern comfortably. A translation ratio is determined for translating the physical distance traversed by the ultrasound signals of an ultrasound images to a corresponding physical distance on a screen of the display device. If the ratio is not below a threshold, the image is displayed in full. If the ratio is below the threshold, the image is cropped, optionally scaled, and displayed in the available area. Scaling and cropping may be based on window size and threshold window size. The parameters of the ultrasound scan may be controlled based on the scaling, cropping, or available screen size. User interface features may be displayed on the screen depending on how much area is available when the image is displayed.

Abstract: A plurality of ultrasound frames of a fetus are acquired using an ultrasound scanner, which may be oriented arbitrarily with respect to the fetus during the acquisition. The ultrasound frames are processed against an artificial intelligence model to predict a different cut line on each of the ultrasound frames. Each cut line is predicted to be exterior to an image of the fetus appearing on the ultrasound frame. The different cut lines on the plurality of ultrasound frames are then used to identify ultrasound data in the image frames to generate a 3D representation of the fetus.

Abstract: Post-scan ultrasound images are masked and labeled with anatomical features identified in the images. Masks corresponding to the features are transformed into the coordinate system of the pre-scan, raw ultrasound data frames corresponding to the images. The masks and their respective raw ultrasound data frames are used to train an artificial intelligence model. The model is then used to predict the presence of anatomical features of the same type in other pre-scan ultrasound data. Once predicted, the raw data is scan converted for display as segmented ultrasound images that identify the predicted anatomical features. Deployment of the model on pre-scan data avoids the need to account for different levels of processing that may be applied to post-scan images, while the labeling for training the model may be done on the post-scan images.

Abstract: The present embodiments relate generally to methods for providing viewing access to an ultrasound image feed generated at an ultrasound imaging machine. A multi-use display device may form a first link-layer connection with the ultrasound image machine for transmitting commands that control imaging parameters of the ultrasound image feed. The multi-use display device may then: determine link-layer connection parameters that allow the ultrasound imaging machine to form a second link-layer connection with a receiving device (the receiving device having no link-layer connection with the ultrasound imaging machine), and provide the connection parameters to the receiving device. The ultrasound imaging machine forms a second link-layer connection with the receiving device, based the connection parameters. The second link-layer connection is then used for receiving, at the receiving device, the ultrasound image feed controlled by the multi-use display device.

Abstract: An ultrasound imaging system comprising a multi-use electronic display device and an ultrasound imaging device. The multi-use electronic display device is capable of communicating with one or more ultrasound imaging devices and selecting which to connect with based on at least one of previously store information, user input, and information gathered from the ultrasound imaging devices. The multi-use electronic display device may communicate with the ultrasound imaging devices while they are in a low power standby state. This approach reduces the complexity of the pairing process and provides a means for quickly and easily selecting between multiple ultrasound imaging devices.

Abstract: A method of creating a 3D model, which is a visual representation of at least one physiological parameter, the method comprises deploying an AI model to execute on a computing device communicably connected to a medical imaging device, said medical imaging device acquiring medical imaging data, wherein the AI model is trained so that when it is deployed, the computing device identifies at least one physiological parameter from medical imaging data; acquiring, at the computing device, new medical imaging data; processing, using the AI model, the new medical imaging data to identify at least one physiological parameter (the “at least one identified physiological parameter”); employing the at least one identified physiological parameter to select a corresponding 3D model; and modifying the corresponding 3D model to alter one or more model parameters therein, to match the at least one identified physiological parameter, thereby customizing the visual appearance of the corresponding 3D model.

Abstract: The present embodiments relate generally to methods for providing viewing access to an ultrasound image feed generated at an ultrasound imaging machine. A multi-use display device may form a first link-layer connection with the ultrasound image machine for transmitting commands that control imaging parameters of the ultrasound image feed. The multi-use display device may then: determine link-layer connection parameters that allow the ultrasound imaging machine to form a second link-layer connection with a receiving device (the receiving device having no link-layer connection with the ultrasound imaging machine), and provide the connection parameters to the receiving device. The ultrasound imaging machine forms a second link-layer connection with the receiving device, based the connection parameters. The second link-layer connection is then used for receiving, at the receiving device, the ultrasound image feed controlled by the multi-use display device.

Abstract: The present embodiments relate generally to a system and method for creation of a patient account on a medical imaging system during a medical imaging examination. The method may involve operating a processor to: acquire a set of medical imaging data during the medical imaging examination, the set of medical imaging data being acquired in association with a logged-in medical professional account on the medical imaging system; display a new patient account prompt to initiate creation of the patient account; receive a patient identifier to initiate the creation of the patient account; and use the patient identifier to initiate the creation of the patient account, the patient account to be used for accessing at least a portion of the set of medical imaging data acquired during the medical imaging examination.

Abstract: A method for positioning one or both of a gate and a color box on an ultrasound image generated during scanning of an anatomical feature using an ultrasound scanner comprises deploying an artificial intelligence (AI) model to execute on a computing device communicably connected to the ultrasound scanner, wherein the AI model is trained so that when the AI model is deployed, the computing device generates a prediction of at least one of an optimal position, size, or angle for the gate and/or an optimal location/size of the color box on the ultrasound image generated during ultrasound scanning of the anatomical feature, thereafter enabling the acquisition of corresponding Doppler mode signals.

Abstract: A plurality of ultrasound frames of a fetus are acquired using an ultrasound scanner, which may be oriented arbitrarily with respect to the fetus during the acquisition. The ultrasound frames are processed against an artificial intelligence model to predict a different cut line on each of the ultrasound frames. Each cut line is predicted to be exterior to an image of the fetus appearing on the ultrasound frame. The different cut lines on the plurality of ultrasound frames are then used to identify ultrasound data in the image frames to generate a 3D representation of the fetus.

Abstract: Ultrasound images are adjusted according to the size of the display area available to display them, so that image detail is displayed with a large enough physical size to discern comfortably. A translation ratio is determined for translating the physical distance traversed by the ultrasound signals of an ultrasound images to a corresponding physical distance on a screen of the display device. If the ratio is not below a threshold, the image is displayed in full. If the ratio is below the threshold, the image is cropped, optionally scaled, and displayed in the available area. Scaling and cropping may be based on window size and threshold window size. The parameters of the ultrasound scan may be controlled based on the scaling, cropping, or available screen size. User interface features may be displayed on the screen depending on how much area is available when the image is displayed.