Ultrasound image devices, systems, and methods are provided. An ultrasound imaging system comprising a processor circuit in communication with an ultrasound transducer array, the processor circuit configured to receive, from the ultrasound transducer array, a set of images of a three-dimensional (3D) volume of a patients anatomy including an anatomical feature; obtain first measurement data of the anatomical feature in a first image of the set of images; generate second measurement data for the anatomical feature in one or more images of the set of images by propagating the first measurement data from the first image to the one or more images; and output, to a display in communication with the processor circuit, the second measurement data for the anatomical feature.

Disclosed is an intraluminal ultrasound imaging system, including a processor circuit in communication with an intraluminal ultrasound imaging catheter, and configured to receive a plurality of intraluminal ultrasound images obtained by the imaging catheter while the imaging catheter is moved through a body lumen of a patient. The processor circuit is further configured to determine a longitudinal translation speed of the imaging catheter based on the plurality of images and a known time interval between images, and display a speed indicator based on the longitudinal translation speed.

A method includes receiving a selection of an examination template including a hierarchical examination workflow and baseline configuration parameters corresponding to the examination template, wherein the examination template is associated with an anatomical area; automatically configuring an imaging system with the baseline configuration parameters from the examination template; capturing image data of a patient using the imaging system according to the hierarchical examination workflow; storing the image data on a storage system, such that the image data is associated with the anatomical area; displaying an anatomical model of a plurality of anatomical areas of the patient; and displaying thumbnails of the image data on respective areas of the anatomical model corresponding to anatomical areas of the patient where the image data was captured by the imaging system.

An ultrasound device (10) includes a probe (12) including a tube (14) sized for insertion into a patient and an ultrasound transducer (18) disposed at a distal end (16) of the tube. A camera (20) is mounted at the distal end of the tube in a fixed spatial relationship to the ultrasound transducer. At least one electronic processor (28) is programmed to: control the ultrasound transducer and the camera to acquire ultrasound images (19) and camera images (21) respectively while the ultrasound transducer is disposed in vivo inside the patient; and construct a keyframe (36) representative of an in vivo position of the ultrasound transducer including at least ultrasound image features (38) extracted from at least one of the ultrasound images acquired at the in vivo position of the ultrasound transducer and camera image features (40) extracted from one of the camera images acquired at the in vivo position of the ultrasound transducer.

An intraoperative ultrasound imaging system and method capable of using ultrasound imaging to safely place a surgical access instrument (e.g. guide wire, dilator, cannula, etc.) through a tissue (e.g., muscle, fat, brain, liver, lung, etc.) without damaging nearby neurovascular structure is described herein. The intraoperative ultrasound system includes an ultrasound probe assembly configured for emitting and receiving ultrasound waves and a computer system including a processor and a display unit. Once the probe is in position, ultrasound imaging is performed wherein the computer receives RF data from the probe and causes a B-mode image of the visible anatomical structures (e.g. muscle, bone, etc.) to be displayed on the display unit.

A method and system provide for the identification of a tendon in ultrasound imaging data, by deploying an artificial intelligence (AI) model to execute on a computing device, wherein the AI model is trained to identify a plurality of different types of tendons imaged in ultrasound imaging data, and when deployed, the computing device generates a probability for each of the plurality of different types of tendons that the type of tendon is imaged in new ultrasound imaging data and wherein such probability is corroborated by at least one live deployment input.

A facility for processing a medical imaging image is described. The facility applies to the image a first machine learning model trained to recognize a view to which an image corresponds, and a second machine learning model trained to identify any of a set of anatomical features visualized in an image. The facility accesses a list of permitted anatomical features for images corresponding to the recognized view, and filters the identified anatomical features to exclude any not on the accessed list. The facility causes the accessed image to be displayed, overlaid with a visual indication of each of the filtered identified anatomical features.

An inspection apparatus includes a measurement apparatus that measures an inner diameter and a blood flow velocity in an artery from a fetus to a placenta of a pregnant woman, a calculation apparatus that calculates a Reynolds number based on the inner diameter and the blood flow velocity in the artery measured by the measurement apparatus, and a determination apparatus that determines, for a pregnant woman who is 20 weeks or more pregnant, that the fetus may be developing FGR in a case that the Reynolds number is less than a first threshold value.

The present embodiments relate generally to systems and methods for acquiring raw ultrasound data from an ultrasound machine using a wirelessly connected device. The systems can be configured to display ultrasound images on a display device and receive input to select the ultrasound images for which to retrieve corresponding raw ultrasound data from the ultrasound machine. A raw data buffer provided at the ultrasound machine may be capable of storing a first time duration of raw ultrasound data. An image display buffer provided at the wireless device may store: processed ultrasound image data corresponding to the raw ultrasound data stored in the raw data buffer; and previously-received processed ultrasound image data that has no corresponding raw ultrasound data stored in the raw data buffer.

Methods and systems are provided for tracking anatomical features across multiple images. One example method includes outputting, for display on a display device, an annotation indicative of a first location of an identified anatomical feature of a first ultrasound image, the annotation generated based on a first output of a model and outputting, for display on the display device, an adjusted annotation based on a second output of the model, the second output of the model generated based on a second ultrasound image and further based on the first output of the model, the adjusted annotation indicative of a second location of the identified anatomical feature in the second ultrasound image.