The present invention provides an ultrasound system, which comprises: a signal acquiring unit to transmit an ultrasound signal to an object and acquire an echo signal reflected from the object; a signal processing unit to control TGC (Time Gain Compensation) and LGC (Lateral Gain Compensation) of the echo signal; a TGC/LGC setup unit adapted to set TGC and LGC values based on TGC and LGC curves inputted by a user; and an image producing unit adapted to produce an ultrasound image of the object based on the echo signal. The signal processing unit is further adapted to control the TGC and the LGC of the echo signal based on the TGC and LGC values set by the TGC/LGC setup unit.

An ultrasound diagnostic apparatus includes an image memory, an operation unit, a measurement item designation receiving unit for receiving a designation of a measurement item, a detection measurement algorithm setting unit that sets a detection measurement algorithm, a frame designation receiving unit that receives a designation of a frame to be used for the measurement among a plurality of frames in the image memory, a measurement position designation receiving unit that receives a designation of a position of a measurement target on a first measurement frame received by the frame designation receiving unit, a measurement position setting unit that sets the position of the measurement target on a frame other than the first measurement frame, a measurement unit that detects the measurement target on the plurality of frames to calculate the measurement value, and a final measurement value calculation unit that calculates a final measurement value.

Aspects of the technology described herein relate to methods and apparatuses for enable a user to manually modify an input to a calculation performed based at least in part on an ultrasound image. In some embodiments, manually modifying the input comprises manually modifying a trace on the image. In some embodiments, manually modifying the input comprises manually selecting an ultrasound image from a series of ultrasound images on which a calculation is to be performed.

A facility identifies anatomical objects visualized by a medical imaging image. The facility applies two machine learning models to the image: a first trained to predict a view probability vector that, for each of a list of views, attributes a probability that the image was captured from the view, and a second trained to predict an object probability vector that, for each of a list of anatomical objects, attributes a probability that the object is visualized by the image. For each object, the facility: (1) accesses a list of views in which the object is permitted; (2) multiplies the predicted probability that the object is visualized by the image by the sum of the predicted probabilities that the accessed image was captured from views in which the object is permitted; and (3) where the resulting probability exceeds a threshold, determines that the object is visualized by the accessed image.

Systems and methods for aiding users in viewing, assessing and analyzing images, especially images of lumens and medical devices contained within the lumens. Systems and methods for interacting with images of lumens and medical devices, for example through a graphical user interface.

Systems and methods for ultrasound imaging include obtaining RF data using an ultrasound probe and processing the RF data in-parallel to generate B-mode data and echo intensity data during ultrasound examination of a patient. The RF data is analyzed in real-time to provide a user with live ultrasound image and echogenicity analytics. Based on the echogenicity analytics, the user may reposition the ultrasonic probe to adjust and select an optimal probe angle to ensure reproducible results. Providing live RF data allows the user to assess the health of nerves and muscles in real-time and make dynamic decisions on further exams to perform during the same office visit.

A hierarchical workflow is configured to associate examination information captured using an imaging platform with contextual metadata. The examination information may include ultrasound image data, which may be associated with annotations, measurements, pathology, body markers, and/or the like. The hierarchical workflow may comprise templates associated with respective anatomical regions, locations, volumes, and/or surfaces. A template may define configuration data to automatically adapt the imaging platform to capture imaging data in the corresponding anatomical region. The template may further include guidance information for the operator, including processing steps for capturing relevant examination information. Additional examination information may be captured and included in the hierarchical workflow.

An ultrasound imaging system comprises a display for displaying a received ultrasound image. A user interface is provided for receiving user commands for controlling the ultrasound imaging process, and it receives a user input which identifies a point or region of the displayed ultrasound image. An image depth is determined which is associated with the identified point or region and the imaging process is controlled to tailor the imaging to the identified point or region.

Provided are a wireless ultrasound probe and an ultrasound imaging apparatus connected with the wireless ultrasound probe. The wireless ultrasound probe includes: a battery; and a charging terminal connector that is coupled to a power supply terminal of the ultrasound imaging apparatus and receives power from the power supply terminal to charge the battery, wherein the charging terminal connector has a unique shape configured to be physically coupled to the power supply terminal.

Aspects of the technology described herein relate to receiving an ultrasound image, automatically determining a location of a specific point on an anatomical structure depicted in the ultrasound image, and displaying an indicator of the location of the specific point on the anatomical structure on the ultrasound image. In some embodiments, the anatomical structure is a bladder. In some embodiments, the specific point is the centroid. In some embodiments, a statistical model determines the specific point. The indicator may be, for example, a symbol located at the specific point, a horizontal line extending through the specific point from one edge of the anatomical structure to another, and/or a vertical line extending through the specific point from one edge of the anatomical structure to another.