Disclosed in the present invention are a method and apparatus for the identification of fetal cross-sections based on ultrasound dynamic images; the method includes: inputting sequentially each frame of fetal ultrasound images from acquired multiple consecutive frames of fetal ultrasound images into a predetermined feature-detecting model for analysis; acquiring a sequentially exported analysis from the feature-detecting model as feature information for each frame of fetal ultrasound images; corresponding to each frame of fetal ultrasound images, identifying a cross-section by the categories of the part and the structural feature. Obviously, for a fetal ultrasound image, the implementation of the present invention may improve the identified accuracy, identified efficiency, and the standardization of the cross-section, by acquiring the part features and structural features from consecutive multi-frame fetal ultrasound images and identifying the cross-section by combining the part features and structural features.

An apparatus includes an imaging probe and is configured for dynamically arranging presentation of visual feedback for guiding manual adjustment, via the probe, of a location, and orientation, associated with the probe. The arranging is selectively based on comparisons between fields of view of the probe and respective results of segmenting image data acquired via the probe. In an embodiment, the apparatus includes a sensor which guides a decision that acoustic coupling quality is insufficient, the apparatus issuing a user alert upon the decision.

A training method and apparatus for angiography image processing and a method and apparatus for automatically processing a vessel image. The training method includes obtaining training data that includes original angiography image data and local segmentation result data of a side branch vessel. The local segmentation result data of the side branch vessel are local segmentation image data of the side branch vessel on a main branch vessel determined from an original angiography image. A neural network is trained according to the obtained training data to make the neural network perform local segmentation on the side branch vessel on the determined main branch vessel in the original angiography image. The training method can obtain the neural network for performing local segmentation on the side branch vessel, thereby realizing improvement of segmentation accuracy while improving segmentation efficiency, and avoiding missing segmentation and wrong segmentation of the side branch vessel.

An ultrasound imaging system includes a cine buffer in which image frames produced during an examination are stored. A processor is programmed to select one or more image frames from the cine buffer for presentation to an operator for approval and inclusion in a patient record or other report. The operator can accept the proposed image frames or can select one or more other image frames from the cine buffer. The processor may select image frames at spaced intervals in the cine buffer for presentation. Alternatively, the processor compares image frames in the cine buffer with one or more target image frames. Image frames that are similar to the target image frames are presented to the operator to confirm. Alternatively, image frames can be selected by the processor that contain a specific feature or that are similar to image frames that were previously selected by the operator when performing a particular type of examination.

A method (900) of generating an atlas for a universal atlas database (901) is provided. A new medical scan image (905) is provided. A universal auto-contouring operation (920) is performed on the medical scan image, to generate a set of universal contours (930) for the medical scan image. A local auto-contouring customisation operation (940) is performed on the medical scan image, to generate a set of local contours (950) for the medical scan image. The set of local contours is standardised (980) using a trained model to compensate for biases in the set of local contours, thereby creating a set of standardised global contours (985) for the medical scan image. The set of standardised global contours (985) and the medical scan image (905) can be added to the universal atlas database (901) as a new atlas, thereby expanding the set of atlases that are available in the universal atlas database.

A medical image processing device of an embodiment includes processing circuitry. The processing circuitry is configured to acquire a contrast-enhanced image of a subject at least after a portal vein dominant phase among contrast-enhanced images of the subject to which a contrast medium has been administered in a process of reaching a post-vascular phase from an artery dominant phase via the portal vein dominant phase, and detect a site where the contrast medium has been washed out as a defective part in the contrast-enhanced image after the portal vein dominant phase.

The disclosure relates generally to the field of vascular system and peripheral vascular system data collection, imaging, image processing and feature detection relating thereto. In part, the disclosure more specifically relates to methods for detecting position and size of contrast cloud in an x-ray image including with respect to a sequence of x-ray images during intravascular imaging. Methods of detecting and extracting metallic wires from x-ray images are also described herein such as guidewires used in coronary procedures. Further, methods for of registering vascular trees for one or more images, such as in sequences of x-ray images, are disclosed. In part, the disclosure relates to processing, tracking and registering angiography images and elements in such images. The registration can be performed relative to images from an intravascular imaging modality such as, for example, optical coherence tomography (OCT) or intravascular ultrasound (IVUS).

Methods and systems for autonomous cardiac mapping are disclosed. An example system for autonomous cardiac mapping of a heart chamber includes a processor being configured to acquire a representative geometric shell of the heart chamber, control a robotic device to autonomously navigate a mapping probe to a plurality of locations within the heart chamber based at least in part on the representative geometric shell, and generate a three-dimensional electroanatomical map of the heart chamber based on electrical data collected by the probe at the plurality of locations.

Systems and methods are disclosed for an ultrasound system. In various embodiments, a system is configured to receive echo data corresponding to a detection of an echo of a pulse signal, generate a set of transformations based on the echo data, and generate a set of point estimates for a frequency dependent filtering coefficient of a spectral response. The system is further configured to extract a set of attenuation coefficients based on the set of point estimates for the frequency dependent filtering coefficient and generate image data for the material of interest based on the set of attenuation coefficients.

Within the field of elastography, a new approach analyzes the limiting case of shear waves established as a reverberant field. In this framework, it is assumed that a distribution of shear waves exists, oriented across all directions in 3D (e.g. 2D space+time). The simultaneous multi-frequency application of reverberant shear wave fields can be accomplished by applying an array of external sources that can be excited by multiple frequencies within a bandwidth, for example 50, 100, 150, . . . 500 Hz, all contributing to the shear wave field produced in the liver or other target organ. This enables the analysis of the dispersion of shear wave speed as it increases with frequency, indicating the viscoelastic and lossy nature of the tissue under study. Furthermore, dispersion images can be created and displayed alongside the shear wave speed images. Studies on breast and liver tissues using the multi-frequency reverberant shear wave technique, employing frequencies up to 700 Hz in breast tissue, and robust reverberant patterns of shear waves across the entire liver and kidney in obese patients are reported. Dispersion images are shown to have contrast between tissue types and with quantitative values that align with previous studies.