Systems, apparatuses, methods, and non-transitory computer-readable media for mapping a section of a vasculature of a subject are described herein, including moving a probe to a first position at a body of the subject adjacent the section of the vasculature; transmitting, by the probe, a first ultrasound beam into a first portion of the section of the vasculature through the body of the subject; receiving first ultrasound data including at least one imaging parameter of the first portion based on the first ultrasound beam; moving the probe to a second position at the body of the subject adjacent the section of the vasculature and different from the first position; transmitting, by the probe, a second ultrasound beam into a second portion of the section of the vasculature through the body of the subject; receiving second ultrasound data including the at least one imaging parameter of the second portion based on the second ultrasound beam; and constructing a map of the section of the vasculature based on the first ultrasound data and the second ultrasound data.

Systems and methods for producing ultrasound images are disclosed herein. In one embodiment, ultrasound image data are acquired in discrete time increments at one or more positions relative to a subject. Control points are added by a user for two or more image frames and a processor interpolates the location of the control points for image frames obtained at in-between times.

Using computer-assisted classification and/or computer-assisted segmentation with or without monitoring the field of view for change, the workflow for ultrasound imaging may be made more efficient. The classification and/or segmentation is used to perform a next act in the sequence of acts making up the ultrasound examination. Rather than requiring a user to determine the act and implement the act, the ultrasound scanner determines and implements the act based on the identification and/or location of an imaged object. For example, the identification of the object as a kidney using a machine-learnt classifier triggers a color flow scan, and the location of the object determines a placement for the color flow region of interest (ROI), avoiding the user having to perform the ROI initiation and/or placement and increasing workflow efficiency.

Provided is a wireless ultrasound probe configured to detect a state in which the wireless ultrasound probe is detached from a charging terminal of an ultrasound diagnostic apparatus, causing supply of the charging power to the wireless ultrasound probe to be discontinued, and the wireless ultrasound probe is paired with the ultrasound diagnostic apparatus by using a wireless communication scheme when supply of the charging power is discontinued. Also provided are an ultrasound diagnostic apparatus and an operating method of the ultrasound diagnostic apparatus configured to be automatically paired with a wireless ultrasound probe in a state in which the wireless ultrasound probe is detached from a charging terminal of the ultrasound diagnostic apparatus, causing supply of the charging power to the wireless ultrasound probe to be discontinued.

An ultrasonic scanning method for an ultrasonic scanning device is provided according to an embodiment of the disclosure. The ultrasonic scanning method includes: performing an ultrasonic scanning operation on a human body by an ultrasonic scanner to obtain an ultrasonic image; analyzing the ultrasonic image by an image recognition module to identify an organ pattern in the ultrasonic image; and generating, automatically, a guiding message according to an identification result of the organ pattern, wherein the guiding message is configured to guide a moving of the ultrasonic scanner to scan a target organ of the human body.

An automated three dimensional mapping and display system for a diagnostic ultrasound system is presented. According to the invention, ultrasound probe position registration is automated, the position of each pixel in the ultrasound image in reference to selected anatomical references is calculated, and specified information is stored on command. The system, during real time ultrasound scanning, enables the ultrasound probe position and orientation to be continuously displayed over a body or body part diagram, thereby facilitating scanning and images interpretation of stored information. The system can then record single or multiple ultrasound free hand two-dimensional (also “2D”) frames in a video sequence (clip) or cine loop wherein multiple 2D frames of one or more video sequences corresponding to a scanned volume can be reconstructed in three-dimensional (also “3D”) volume images corresponding to the scanned region, using known 3D reconstruction algorithms. In later examinations, the exact location and position of the transducer can be recreated along three dimensional or two dimensional axis points enabling known targets to be viewed from an exact, known position.

An ultrasound diagnostic device including an ultrasound image acquirer that acquires a plurality of ultrasound image signal frames; an angle information acquirer that acquires angle information of an ultrasound probe when each frame is being acquired; an evaluation determiner that analyzes the frames to determine whether an object image portion is included; a disease score calculator that calculates a disease score that quantitatively indicates a degree of disease from a signal of the object image portion; and a display controller that makes the diagnostic image be displayed. A diagnostic image includes an ultrasound image of a frame selected from the frames, a disease activity information indicator that indicates a degree of disease, and an angle information image portion that indicates angle information.

A system for automatically determining a thickness of a wall of an artery of a subject includes an ECG monitoring device that captures an electrocardiogram (ECG) signal from the subject, and an ultrasound video imaging device, coupled to the ECG monitoring device, that receives the ECG signal from the ECG monitoring device, and captures a corresponding ultrasound video of the wall of the artery of the subject. The system produces a plurality of frames of video comprising the ultrasound video of the wall of the artery of the subject and an image of the ECG signal. A processor is configured to select a subset of the plurality of frames of the ultrasound video based on the image of the (ECG) signal, locate automatically a region of interest (ROI) in each frame of the subset of the plurality of frames of the video using a machine-based artificial neural network and measure automatically a thickness of the wall of the artery in each ROI using the machine-based artificial neural network.

Provided is an object information acquiring apparatus, including: a light source; a detecting unit that detects an acoustic wave generated from an object which has received an irradiation light from the light source; a processing unit that generates characteristic information on the inside of the object by using the acoustic wave; and a memory unit that records the characteristic information in association with information on the irradiation light.

A method is disclosed for generating sinograms by sampling a plurality of transducers acoustically coupled with the surface of a volume of tissue over a period of time after a light pulse at one wavelength, and after another light pulse at a different wavelength, and for processing those sinograms, reconstructing at least two optoacoustic images from the two sinograms, processing the two optoacoustic images to generate two envelope images and generating a parametric map from information in the two envelope images. In an embodiment, motion and tracking are determined to align the envelope images. In an embodiment, at least a second parametric map is produced from information in the same two envelope images. In an embodiment an ultrasound image is also acquired, and the parametric map is coregistered with and overlayed upon the ultrasound image, and then displayed.