Ultrasound image devices, systems, and methods are provided. An ultrasound imaging system comprising a processor circuit configured to receive, from an ultrasound transducer array, a plurality of images of a patient body at different imaging planes; determine a first imaging plane based on a first image of the plurality of images by applying a first predictive network, wherein a second image of the plurality of images is based on the first imaging plane, and wherein the second image includes an imaging view of at least one of an anatomy of the patient body or a medical device within the anatomy; apply a second predictive network to the second image to generate segmentation data; and output, to a display, a displayed image including an indication of a first portion of the at least one of the anatomy or the medical device based on the segmentation data.

Implementations described and claimed herein provide systems and methods for managing one or more patients. In one implementation, an imaging window is determined based on a location of a probe. A primary image cross-section for the imaging window is identified for the imaging window. At least one image is generated along the primary image cross-section using patient data captured using the probe. The at least one image is compared to an expected image contour scaffold of the primary image cross-section. The probe is commanded to fine-tune an imaging plane based on the comparison until the at least one image matches the expected image contour scaffold of the primary image cross-section.

According to various embodiments, there is provided a device including a processor configured to control a robotic system to autonomously position a transducer at a plurality of locations adjacent a subject's skull and to autonomously locate a window on the subject's skull within which an artery can be located, from which artery a signal can be returned to the transducer, the signal having an energy level exceeding a predefined threshold.

An ultrasound diagnostic apparatus 1 includes an image acquisition unit 3 that generates an ultrasound image, an image recognition unit 9 that performs image recognition for the ultrasound image to calculate recognition scores, an index value calculation unit 10 that calculates index values of a plurality of parts on the basis of the recognition scores calculated for a predetermined number of ultrasound images, an order decision unit 11 that decides a determination order in which part determination is performed for the plurality of parts on the basis of the index values, and a part determination unit 12 that determines an imaging part of a subject on the basis of the recognition scores calculated according to the determination order.

An interface unit (12) for connecting between an ultrasound sensing apparatus (14) and a patient monitor (18) for providing ultrasound monitoring functionality of one or more physiological or anatomical parameters based on processing of ultrasound data. The interface unit includes means for processing acquired ultrasound data to derive measurements of one or more physiological or anatomical parameters and is configured for outputting said derived measurements to a coupled patient monitor unit, e.g. for display and/or trending by the patient monitor.

Machine learning trains to tune settings. For training, the user interactions with the image parameters (i.e., settings) as part of ongoing examination of patients are used to establish the ground truth positive and negative examples of settings instead of relying on an expert review of collected samples. Patient information, location information, and/or user information may also be included in the training data so that the network is trained to provide settings for different situations based on the included information. During application, the patient is imaged. The initial or subsequent image is input with other information (e.g., patient, user, and/or location information) to the machine-trained network to output settings to be used for improved imaging in the situation.

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.

Aspects of the technology described herein relate to configuring an ultrasound system with imaging parameter values. In particular, certain aspects relate to configuring an ultrasound system to produce a plurality of sets of ultrasound images, each respective set of the plurality of sets of ultrasound images being produced with a different respective set of a plurality of sets of imaging parameter values; obtaining, from the ultrasound system, the plurality of sets of ultrasound images; determining a set of ultrasound images from among the plurality of sets of ultrasound images that has a highest quality; and based on determining the set of ultrasound images from among the plurality of sets of ultrasound images that has the highest quality, automatically configuring the ultrasound system to produce ultrasound images using a set of imaging parameter values with which the set of ultrasound images that has the highest quality was produced.

The present disclosure relates to a method for configuring a medical device. The method comprises: providing a set of one or more parameters for configuring the medical device. Each parameter of the set has predefined values. A set of values of the set of parameters may be selected from the predefined values. Using the selected values the set of parameters may be set, which results in an operational configuration of the medical device. The medical device may be controlled to operate in accordance with the operational configuration, thereby an operating status of the medical device may be determined. Based on at least the operating status the operational configuration may be maintained or the selecting, setting and controlling may be repeatedly performed until a desired operating status of the medical device can be determined based on the operating statuses resulting from the controlling.

Provided are a medical diagnosis apparatus and a medical diagnosis method using the same. According to an embodiment, the medical diagnosis apparatus may include: a main body; a chair unit movably supported by the main body and on which an object is positioned; a diagnosis part that is movably connected to the main body and is spaced apart from the chair unit by a preset first distance in one plane; a controller configured to generate a control signal for moving the diagnosis part according to preset information; and a first driving device configured to generate a driving force for moving the diagnosis part according to the control signal.