A peer-review flagging system is operable to receive a medical scan and a medical report written by a medical professional in conjunction with review of the medical scan. Automated assessment data is generated by performing an inference function on the medical scan by utilizing a computer vision model trained on a plurality of medical scans. Human assessment data is generated by performing an extraction function on the medical report. Consensus data is generated by comparing the automated assessment data to the first human assessment data. A peer-review notification is transmitted to a client device for display. The peer-review notification indicates the medical scan is flagged for peer-review in response to determining the consensus data indicates the automated assessment data compares unfavorably to the human assessment data.

Provided is a non-invasive system and method for determining a fuel value for a target muscle and potentially at least one indicator muscle. The method includes receiving an ultrasound scan of a target muscle; evaluating at least a portion of the ultrasound scan to determine fuel value within the target muscle; recording the determined fuel value for the muscle as an element of a data set for the muscle; evaluating the fuel data set to determine a value range; and in response to the range being at least above a pre-determined threshold, establishing a target score for the muscle as based on an upper portion of the value range. The method may be repeated to identify ranges for a plurality of muscles, the muscle with the greatest range being identified as an indicator muscle. Based on these findings the muscles estimated fuel level, fuel rating and energy status may be determined. An associated system is also disclosed.

Ultrasound imaging devices, systems, and methods are provided. A guidance system for obtaining an ultrasound image, comprising a processor in communication with a camera and a display, the processor configured to obtain a first motion control configuration for repositioning an ultrasound imaging device from a first position towards a target image view of a subject's anatomy, the first motion control configuration determined based on a first predictive network; determine positional information associated with the ultrasound imaging device based on an image captured by the camera, the image including the subject's anatomy and the ultrasound imaging device positioned at the first position; and output, to the display, an instruction to reposition the ultrasound imaging device from the first position to a second position based on the first motion control configuration and the positional information associated with the ultrasound imaging device.

An ultrasound diagnostic apparatus includes: an array transducer in which a plurality of elements are arranged; a transmitting unit that transmits an ultrasound beam to a subject; a receiving unit that receives ultrasound echoes from the subject to acquire element data; an element data analysis unit that analyzes the element data to acquire element data information; a collation pattern database in which a plurality of collation patterns that are associated with a plurality of examination parts of the subject and are related to the element data information are stored in advance; and a part recognition unit that collates the element data information using the collation pattern to perform part recognition determining from which examination part of the subject the ultrasound echoes have been reflected.

A method for determining a projected track of an object (230) includes measuring movement from frame to frame of a detected object point in a field of view by periodic comparison of positions, extrapolating a locus of periodically detected object points, and qualifying the locus by calculating and applying a threshold to the linearity in a sequence of positions and a threshold to consistency in strength. The method further produces the plurality of ultrasound images by including thereon a rendering of a plurality of lines (310) as a path track indicator (330) on one or more ultrasound images (305) and displaying the projected track of the object when a user moves the tracked object a minimum distance in a region of interest (242) of a subject (240). The method also includes utilizing a motion sensor (234) with a probe (205) to suppress calculation and display of the projected track.

Aspects of the technology described herein relate to techniques for guiding an operator to use an ultrasound device. Thereby, operators with little or no experience operating ultrasound devices may capture medically relevant ultrasound images and/or interpret the contents of the obtained ultrasound images. For example, some of the techniques disclosed herein may be used to identify a particular anatomical view of a subject to image with an ultrasound device, guide an operator of the ultrasound device to capture an ultrasound image of the subject that contains the particular anatomical view, and/or analyze the captured ultrasound image to identify medical information about the subject.

An imaging method for obtaining a human skeleton, comprising the following steps: S1. determining a target region and fixing an object to be scanned; S2. determining an imaging region; S3. scanning the target region to obtain a series of section images that record spatial position coordinates and scanning angle of the imaging probe; S4. determining the position of bones in a three-dimensional space according to the features reflected on the surfaces of the bones in the section images and the spatial position coordinates and scanning angle of the imaging probe, and obtaining position information of the bones; S6. continuously scanning the target region till the position information and section images of the bones in the skeleton in the entire target region are completely collected; and S7. displaying the skeleton in the three-dimensional space. By means of the method, the human skeleton structure can be obtained without radiation.

The present disclosure describes systems and methods configured to determine shear wave velocity and tissue stiffness levels of thin tissue of finite size, also referred to as bounded tissue, via shear wave elastography. Systems can include an ultrasound transducer configured to acquire echoes responsive to pulses transmitted toward a tissue. Systems can also transmit a push pulse into the tissue for generating shear waves, and tracking pulses intersecting the shear waves. The system can also apply a directional filter to received echo data and generate directionally filtered shear wave data based on a dimension and angular orientation of the bounded target relative to the ultrasound transducer. The system can estimate velocities of the shear waves at different shear wave frequencies based on the filtered shear wave data and angular orientation relative to the transducer, and determine a tissue stiffness value independent of the shape or form of the tissue.

Described here are systems and methods for generating quantitative flow mapping from medical flow data (e.g., medical images, patient-specific computational flow models, particle image velocimetry data, in vitro flow phantom) over a virtual volume representative of a catheter or other medical device. As such, quantitative flow mapping is provided with reduced computational burdens. Quantitative flow maps can also be generated and displayed in a manner that is similar to catheter-based or other medical device-based mapping, without requiring an interventional procedure to place the catheter or medical device.

A medical scan system is operable to receive a set of labeling data corresponding to a set of medical scans from each of a set of client devices corresponding to a set of users. The set of medical scans and each set of labeling data is transmitted to an expert client device associated with an expert user, and a set of golden labeling data and a plurality of sets of correction data are received from the expert client device. A set of performance score data is generated based on the plurality of sets of correction data, and each performance score data of the set of performance score data is assigned to a corresponding one of the set of users. An updated training set that includes the set of golden labeling data is generated, and a medical scan analysis function is retrained based on the updated training set.