An image matting method and apparatus, an electronic device, and a computer-readable storage medium. The method comprises: performing feature point detection on an image so as to obtain a feature point; acquiring a first image region manually marked on the image; adjusting the first image region according to the feature point, so as to obtain a second image region; and performing matting on the image according to the second image region. The manually marked first image region is adjusted according to the feature point, so as to acquire the second image region which is more accurately positioned, and then matting can be performed according to the second image region so as to accurately extract a required region.

A measurement method, which is performed by a measurement device that measures a displacement of a target object, includes: receiving designation of a designation point on a first image that includes the target object; setting a plurality of set points, based on the designation point; identifying a direction of a line that connects two of the plurality of set points; generating a second image by rotating the first image, the second image being an image in which the identified direction of the line is horizontal or vertical; setting, in the second image, a measurement region that partially includes the line; and measuring the displacement of the target object in the measurement region, the displacement being a displacement in a direction orthogonal to the line.

A method includes calculating a first medial-axis tree graph of a volume of an organ of a patient in a first computerized anatomical map of the volume, acquired at a first time. A second medial-axis tree graph is calculated, of a volume of the organ of the patient in a second computerized anatomical map of the volume, acquired at a second time that is different from the first time. A deviation is detected and estimated, between the first and second tree-graphs. Using the estimated deviation, the first and second medial-axis tree graphs are registered with one another. Using the registered first and second tree graphs, the first and second computerized anatomical maps are combined.

A bronchial stent includes a first branch configured to widen, open, and/or mechanically support a first airway; an obstructive portion that, when the stent is deployed in the first airway, obstructs a second airway, the second airway forming a branching connection with the first airway; and a feature proximal to the obstructive portion, the feature configured to facilitate opening of the obstructive portion.

A system for patient cardiac imaging and tissue modeling. The system includes a patient imaging device that can acquire patient cardiac imaging data. A processor is configured to receive the cardiac imaging data. A user interface and display allow a user to interact with the cardiac imaging data. The processor includes fat identification software conducting operations to interact with a trained learning network to identify fat tissue in the cardiac imaging data and to map fat tissue onto a three-dimensional model of the heart. A preferred system uses an ultrasound imaging device as the patient imaging device. Another preferred system uses an MRI or CT image device as the patient imaging device.

The present embodiments relate generally to systems and methods for performing a measurement on an ultrasound image displayed on a touchscreen device. The method may include: receiving, via the touchscreen device, first input coordinates corresponding to a point on the ultrasound image; using the first input coordinates as a seed for performing a contour identification process on the ultrasound image, wherein the contour identification process performs contour evolution using morphological operators to iteratively dilate from the first input coordinates; upon identification of a contour from the contour identification process, placing measurement calipers on the identified contour; and storing a value identified by the measurement calipers as the measurement.

A method of displaying a nearby point of interest (POI) using augmented reality and an electronic device thereof. An operation method of an electronic device includes: acquiring a preview video; acquiring location information of the electronic device; acquiring information on at least one POI located in a vicinity; selecting a focus POI among at least one POI; determining first information to be provided to a user for general POIs; determining second information including more information than the first information to be provided to the user for the focus POI; determining a location on a screen on which the preview video in which the information on the at least one POI is to be displayed; and displaying the first information or the second information on the location on the screen on which the determined preview video of all or some of the at least one POI is provided.

The present disclosure is directed to a computer-implemented method and system for anatomical tree structure analysis. The method includes receiving model inputs for a set of positions in an anatomical tree structure. The method further includes applying, by a processor, a set of encoders to the model inputs. Each encoder is configured to extract features from the model input at a corresponding position. The method also includes applying, by the processor, a tree structured network to the extracted features. The tree structured network has a plurality of nodes each connected to one or more of the encoders, and information propagates among the nodes of the tree structured network according to spatial constraints of the anatomical tree structure. The method additionally includes providing an output of the tree structured network as an analysis result of the anatomical tree structure analysis.

Aspects of the disclosure include methods, apparatuses, and non-transitory computer-readable storage mediums for generating a three-dimensional (3D) geometry of a room from a panorama image of the room. An apparatus includes processing circuitry that determine two-dimensional (2D) positions of wall corner points of the room in the panorama image based on a user input. Each wall corner point is in one of a floor plane or a ceiling plane of the room. The processing circuitry calculates 3D positions of the wall corner points based on the 2D positions of the wall corner points, a size of the panorama image, and a distance between the floor plane and a capture position of a device capturing the panorama image, determines a room layout based on an order of the wall corner points, and generates the 3D geometry based on the room layout and the 3D positions of the wall corner points.

A robot automatically annotates items by training a semantic segmentation module. The robot includes one or more imaging devices, and a controller comprising machine readable instructions. The machine readable instructions, when executed by one or more processors, cause the controller to capture an image with the one or more imaging devices, identify a target area in the image in response to one or more points on the image designated by a user, obtain depth information for the target area, calculate a center of an item corresponding to the target area based on the depth information, rotate the imaging device based on the center, and capture an image of the item at a different viewing angle in response to rotating the view of the imaging device.