Verathon Inc.

Fuxing Yang

Joon Hwan Choi

Gerald J McMorrow

Stephen Dudycha

Monali Padwal

Kendall R Waters

Nasser Saber

Vikram Chalana

Jongtae Yuk

Si Luo

Nikolas Ivancevich

Yanwei Wang

Dave Scott

Susannah Helen Bloch

Steven J Shankle

Jeremiah DeHaan

Gerald Mcmorrow

A system may include an ultrasound probe and a controller unit configured to aim the ultrasound probe to transabdominally image a patient's prostate and obtain a transabdominal image of the patient's prostate using the aimed ultrasound probe. The controller unit may be further configured to perform a segmentation process on the obtained transabdominal image of the patient's prostate using a trained machine learning model to identify a boundary of the prostate in the transabdominal image of the patient's prostate.

Automated prostate analysis system

A track-based scanning system uses an ultrasound probe that is mechanically guided through incremental scans over an area of interest. The scanning system can be configured for different patient applications using interchangeable track stands. Two-dimensional scan data and probe position information are fed back to a base unit for processing and assembly of a three-dimensional (3D) shape model. 3D abdominal aorta segmentation and other type of analysis may be performed based on a 3D vascular shape model and an intensity model.

Systems and methods for 3D ultrasound imaging of extended targets using interchangeable track stands

A system includes a number of transducers configured to transmit ultrasound signals directed to a target blood vessel and receive echo information associated with the transmitted ultrasound signals. The system also includes a processing device configured to process the echo information, generate ultrasound images of the blood vessel at a number of locations and generate an estimated diameter of the blood vessel at the locations. The processing device is also configured to output image information associated with the blood vessel and output a maximum estimated diameter of the blood vessel or the estimated diameters at the number of locations based on the image information.

Systems and methods for ultrasound scanning

A system may include an ultrasound probe and a controller unit configured to communicate with the ultrasound probe. The controller unit may be further configured to select an aiming mode for the ultrasound probe; select a first aiming mode plane, scanning mode, or imaging mode; select at least one additional aiming mode plane, scanning mode, or imaging mode; toggle between obtaining and displaying ultrasound images associated with the first aiming mode plane, scanning mode, or imaging mode and obtaining and displaying ultrasound images associated with the at least one additional aiming mode plane, scanning mode, or imaging mode; receive a selection of a three-dimensional (3D) scan mode; and perform a 3D scan using the ultrasound probe, in response to receiving the selection of the 3D scan mode.

Multi-plane and multi-mode visualization of an area of interest during aiming of an ultrasound probe

A system includes a probe configured to transmit ultrasound signals directed to a target blood vessel and receive echo information associated with the transmitted ultrasound signals. The system also includes at least one processing device configured to process the received echo information and generating a three-dimensional ultrasound image of the target blood vessel; obtain a three-dimensional vascular model corresponding to the target blood vessel; identify a best-fit of the three-dimensional vascular model onto the three-dimensional target image; store the best fit of the three-dimensional vascular model as a segmentation result; and calculate, based on the segmentation result, measurements for the target blood vessel.

Systems and methods for quantitative abdominal aortic aneurysm analysis using 3D ultrasound imaging

A system may include an ultrasound probe and a controller unit configured to obtain a baseline ultrasound image of a patient's breast area using the ultrasound probe and to obtain a follow-up ultrasound image of the patient's breast area using the ultrasound probe. The controller unit may further be configured to use one or more machine learning models to compare the baseline ultrasound image with the follow-up ultrasound image; detect a change in a morphology or integrity of the patient's breast area based on the comparison of the baseline ultrasound image with the follow-up ultrasound image; and generate a recommendation for a medical intervention based on the detected change.

Implant assessment using ultrasound and optical imaging

A system may include an ultrasound probe and a controller unit configured to communicate with the ultrasound probe. The controller unit may be further configured to transmit ultrasound signals using the ultrasound probe toward an area of interest in a patient's body, wherein the ultrasound signals include a fundamental frequency signal and at least one harmonic frequency signal; receive echo signals from the area of interest based on the transmitted ultrasound signals; obtain a fundamental frequency echo signal and at least one harmonic frequency echo signal from the received echo signals; and generate a visual representation of the area of interest based on the obtained fundamental frequency echo signal and the obtained at least one harmonic frequency echo signal.

Multiple frequency scanning using an ultrasound probe

A system includes an ultrasound probe comprising an ultrasound transducer, a first motor configured to rotate the ultrasound transducer around a horizontal axis to scan a plane, and a second motor configured to rotate the ultrasound transducer around a vertical axis to move to a different plane. The system further includes a controller unit configured to select a number of scan planes for an interlacing scan to scan a volume of an area of interest in a patient's body using the ultrasound probe; select an interlacing factor for the interlacing scan; divide the scan planes into groups of scan planes based on the interlacing factor; and perform the interlacing scan by controlling the first motor and the second motor, wherein the first motor moves in a first direction for at least some of the scan planes and in a second direction for other ones of the scan planes.

Generalized interlaced scanning with an ultrasound probe

A method for providing artifact detection and visualization during ultrasound image collection is performed by a processor in an ultrasound system. The method includes receiving ultrasound image data from an ultrasound probe, detecting areas with artifacts in the ultrasound image data, classifying the areas with artifacts into one of a plurality of available artifact classes, generating an indication of the areas with artifact for an ultrasound-based image, wherein the indications include a designation of the artifact class, and presenting to an operator the ultrasound-based image and the indication of the areas with artifacts.

Echo window artifact classification and visual indicators for an ultrasound system

A bladder monitoring system includes a scanning system and a wearable bladder monitoring device (or patch). The scanning system obtains scan data that shows a bladder in a patient and identifies, based on the scan data, a placement location on the patient for the wearable bladder monitoring device. The scanning system indicates the placement location to a user; and identifies customization settings for one or more sensors of the wearable bladder monitoring device to enable the one or more sensors to detect extents of the bladder when the wearable bladder monitoring device is attached at the placement location.

Bladder monitoring system

A system includes a probe configured to transmit ultrasound signals to a target blood vessel, and receive echo information associated with the transmitted ultrasound signals. The system may also include at least one processing device configured process the received echo information and generate an ultrasound image of the blood vessel and identify a seed position within the blood vessel based on the ultrasound image. The at least one processing device may further generate an estimated contour for a lumen of the blood vessel based on pixel intensity values associated with the ultrasound image, generate an estimated contour for the blood vessel using the pixel intensity values, determine whether a thrombus exists within the blood vessel and output image information illustrating the estimated contours of the lumen and the blood vessel.

Thrombus detection during scanning

A method for determining a contour of an organ in an ultrasound image is performed by a processor in a base unit. The method includes detecting an organ within the ultrasound image; obtaining a centroid position for the organ; extending a set of radial lines from the centroid position beyond an expected organ boundary; determining cost values at candidate nodes on each radial line, of the set of radial lines, by applying costs along gradient vectors that are normal to a contour between adjacent nodes on different radial lines; and selecting a final organ boundary contour based on a cost function analysis of paths through the candidate nodes.

Active contour model using two-dimensional gradient vector for organ boundary detection

Systems and methods are described for acquiring, processing, and presenting boundaries of a cavity-tissue interface within a region-of-interest in an ultrasound image based upon the strength of signals of ultrasound echoes returning from structures within the region-of-interest. The segmentation of boundaries of cavity shapes occupying the region-of-interest utilizes cost function analysis of pixel sets occupying the cavity-tissue interface. The segmented shapes are further image processed to determine areas and volumes of the organ or structure containing the cavity within the region-of-interest.

System and method to identify and measure organ wall boundaries

Systems, methods, and devices for image clarity of ultrasound-based images are described wherein motion sections are compensated with the still sections of the region of interest. Velocity map analysis of regions-of-interest is determined to compensate for instrument motion from motions attributable to structures within the region of interest. Methods include image processing algorithms applied to collected echogenic data sets and the dispensers that use apply air-expunged sonic coupling mediums.

Systems and methods to improve clarity in ultrasound images

Systems, methods, and ultrasound transceivers equipped and configured to execute harmonic analysis and extract harmonic information related to a targeted organ of a subject are described. The methods utilize neural network algorithms to establish improved segmentation accuracy of the targeted organ or structures within a region-of-interest. The neural network algorithms, refined for detection of the bladder and to ascertain the presence or absence of a uterus, is optimally applied to better segment and thus confer the capability to optimize measurement of bladder geometry, area, and volumes.

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Bothell, WA, United States of America

Fuxing Yang