A medical scan triaging system is operable to train a computer vision model and to generate abnormality data indicating abnormality probabilities for medical scans via the computer vision model. A first subset of medical scans is determined by identifying medical scans with abnormality probabilities greater than a first probability value of a triage probability threshold. A second subset of medical scans is determined by identifying medical scans with abnormality probabilities less than the first probability value. An updated first subset of medical scans is determined by identifying medical scans with abnormality probabilities greater than a second probability value of an updated triage probability threshold. An updated second subset of the plurality of medical scans is determined by identifying medical scans with a abnormality probabilities less than the second probability value. The updated first subset of medical scans is transmitted to client devices.

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 thereon, the muscles estimated fuel level, fuel rating and energy status may be determined.

A catheter system includes a catheter. The catheter includes a catheter tip and an ultrasound assembly at least partially positioned within the catheter tip. The ultrasound assembly includes a first optical fiber coupled to an optical-to-ultrasound transducer and a second optical fiber coupled to an ultrasound-to-optical transducer. The optical-to-ultrasound transducer is configured to generate an ultrasound signal in response to a pulsed optical signal. The ultrasound-to-optical transducer is configured to generate an optical signal in response to a received ultrasound signal.

Apparatus and methods are described including, using a computer processor (28), automatically identifying whether a given pixel (111) within an image corresponds to a portion of an object. A set of concentric circles (132a-c) that are disposed around the pixel are sampled, and a first function is applied to each of the circles such that the circles are defined by a first set of rotationally invariant descriptors. A second function is applied to the set of circles to generate a second set of descriptors, each of which represents a difference between respective pairs of the circles. A third function is applied such that the second set of descriptors becomes rotationally invariant. The processor identifies whether the given pixel corresponds to the portion of the object, based upon the first and second sets of rotationally invariant descriptors. Other applications are also described.

According to the present invention, when measurement of a distance (fetal head biparietal diameter) on an ultrasonic image is started, a first mobile marker for designating a start point and a standard range display graphic are displayed. The standard range display graphic is a graphic that is centered on the first mobile marker and comprises two circular graphics having radii that are configured to be a lower limit and upper limit of a fetal head biparietal diameter standard range. A user can designate the start point while recognizing, via the standard range display graphic, an end point candidate range. Subsequently, an end point can be designated while recognizing the end point candidate range via a stationary standard range display graphic.

According to one embodiment, an ultrasonic diagnostic apparatus includes an image acquisition unit configured to acquire an ultrasonic image, a first calculation unit which calculates directions of edges in a local region in the ultrasonic image, sizes of the edges in the local region, and directional uniformity of the edges in the local region, a second calculation unit which calculates a composite coefficient by using the sizes of the edges and the directional uniformity of the edges, a third calculation unit which calculates a filtering coefficient for a region corresponding to the local region based on the composite coefficient, and a filtering unit which performs filtering processing for sharpening or smoothing the ultrasonic image with respect to the ultrasonic image by using the filtering coefficient.

A medical image processing apparatus according to an embodiment includes a processing circuit. The processing circuit specifies teaching data used for generation of a learned model. The processing circuit performs image analysis with respect to pieces of collected medical image data. The processing circuit extracts medical image data having an attribute common to the teaching data of the learned model from the pieces of medical image data based on an analysis result of the image analysis, as a candidate of the teaching data of the learned model.

A peer-review flagging system is operable to train a computer vision model and to generate automated assessment data by performing an inference function on a first medical scan by utilizing the computer vision model. Human assessment data is generated based on a first medical report written by a medical professional in conjunction with review of the first medical scan. First consensus data is generated based on the automated assessment data, the human assessment data, and a first threshold, and the first medical scan is determined to be flagged based on the first consensus data. A second threshold is selected use in generating second consensus data for a second medical scan and a second medical report written by the medical professional in conjunction with review of the second medical scan, and is selected to be stricter than the first threshold based on determining to flag the first medical scan.

The present invention provides a method for storing an ultrasonic scan image and an ultrasonic device. The ultrasonic device may include: an image acquiring unit configured to scan a target object to obtain an image; a buffer unit configured to store the obtained image; a processing unit configured to compute a similarity of a frame of the image; and a storage unit, wherein when it is determined that the computed similarity of the frame is less than a threshold, the processing unit stores frames with a similarity equal to or greater than the threshold previous to the frame in the storage unit. Therefore, the image may be stored automatically based upon the similarity information of the frame of the ultrasonic scanning image.

Pose of an ultrasound transducer is recovered. In one approach, inertial measurement units are positioned on the ultrasound transducer. The measurements from the inertial measurement units are used with pose or measurements from another position sensor (e.g., x-ray, electromagnetic, or optical) to improve accuracy and/or provide pose information at a greater rate. In another approach, a curve, line, or other connected shape of light emitting diodes are incorporated into the transducer. Optical tracking, with a filter specific to the light emitting diodes, using the connected shape pattern is used to determine the pose.