An ultrasound diagnostic apparatus includes: a display unit that displays an acoustic wave image; an operation unit for a user to perform an input operation; a measurement item designation receiving unit that receives designation of a measurement item relevant to a measurement target; a detection measurement algorithm setting unit that sets a detection measurement algorithm based on the measurement item; a position designation receiving unit that receives designation of a position of a measurement target on the acoustic wave image; a measurement unit that detects the measurement target from the acoustic wave image based on the position of the measurement target and the detection measurement algorithm, measures the measurement target, calculates a measurement candidate, and displays the measurement candidate on the display unit; and a measurement candidate designation receiving unit that receives designation of the measurement candidate in a case where a plurality of measurement candidates are displayed.

Methods and systems are provided for optimal segmentation of an image based on multiple segmentations. In particular, multiple segmentation methods can be combined by taking into account previous segmentations. For instance, an optimal segmentation can be generated by iteratively integrating a previous segmentation (e.g., using an image segmentation method) with a current segmentation (e.g., using the same or different image segmentation method). To allow for optimal segmentation of an image based on multiple segmentations, one or more neural networks can be used. For instance, a convolutional RNN can be used to maintain information related to one or more previous segmentations when transitioning from one segmentation method to the next. The convolutional RNN can combine the previous segmentation(s) with the current segmentation without requiring any information about the image segmentation method(s) used to generate the segmentations.

This application provides a pose determining method performed by an electronic device. The method includes: determining a first two-dimensional plane point in a first video frame captured by a camera, in response to a user-selected point within a display region of a target horizontal plane in a real world captured in the first video frame; obtaining first orientation information of the camera when acquiring the first video frame; determining a first three-dimensional space point corresponding to the first two-dimensional plane point in the real world and first coordinates of the first three-dimensional space point in a camera coordinate system; and determining a pose of the camera when acquiring the first video frame in the world coordinate system, according to the first orientation information of the camera and the first coordinates of the first three-dimensional space point in the real world.

A method for locating at least one point of a real part on a virtual part defined in a first coordinate system by targeting the point of the real part with a pointer of an augmented-reality device. The method includes determining a transfer matrix for converting between a coordinate system in which the pointer moves and a coordinate system in which the virtual part corresponding to the real part is defined, and determining the coordinates in the first coordinate system of the point be located by converting, by virtue of the transfer matrix, the coordinates in the second coordinate system of the pointer pointed at the point to be located.

A computer-implemented method to improve the point collection process during registration of a bone for a computer-assisted surgical procedure is provided. Based on bone digitization data, a simulation is performed to confirm the accuracy of the registration for different digitization regions. Results are tested to identify which digitization regions meet a predefined accuracy requirement. The resulting information is used to perform a computer-assisted surgical procedure. A computerized simulation method for registration of a bone for a computer-assisted surgical procedure is also provided based on processor executing random stroking an expected exposed surface of a bone model with multiple of stroke curves to cover most of the bone model surface with uniform noise and a random sample consensus is applied to remove outlying point to yield the best registration results, to find the top subset as to overlap. A method to perform computer-assisted surgery is also provided.

Disclosed are a bone age estimation method and a bone age estimation apparatus. The bone age estimation method may comprise the steps of: extracting a region of interest including a cervical spine region from a lateral cephalometric radiographic image obtained by imaging a subject's cervical spine, by using a first deep learning model; extracting landmarks from the extracted region of interest by using a second deep learning model; calculating a landmark numerical value on the basis of the extracted landmarks; and providing maturity information of a maturation stage of the cervical spine on the basis of the calculated landmark numerical value.

Techniques are disclosed for aligning fiducial markers that commonly exist in each of multiple different N-dimensional (N-D) data sets. Notably, the N-D data sets are at least three-dimensional (3D) data sets. A first set and a second set of N-D data are accessed. A set of one or more fiducial markers that commonly exist in both those sets are identified. Based on the fiducial markers, one or more transformations are performed to align the two sets. Performing this alignment process results in at least a selected number of the common fiducial markers that exist in the two sets being within a threshold alignment relative to one another.

A map generation device (10) generates linearization information expressing at least one or the other of a marking line of a roadway and a road shoulder edge based on measurement information of a periphery of the roadway. The measurement information is obtained by a measurement device. The map generation device (10) calculates an evaluation value expressing a reliability degree of partial information, for each partial information constituting the linearization information. A map editing device (20) displays the partial information in different modes according to the evaluation value, thereby displaying the linearization information. The map editing device (20) accepts input of editing information for the displayed linearization information.

Systems and methods for identifying and assessing lymph nodes are provided. Medical image data (e.g., one or more computed tomography images) of a patient is received and anatomical landmarks in the medical image data are detected. Anatomical objects are segmented from the medical image data based on the one or more detected anatomical landmarks. Lymph nodes are identified in the medical image data based on the one or more detected anatomical landmarks and the one or more segmented anatomical objects. The identified lymph nodes may be assessed by segmenting the identified lymph nodes from the medical image data and quantifying the segmented lymph nodes. The identified lymph nodes and/or the assessment of the identified lymph nodes are output.

Systems and methods for utilizing Augmented Reality (AR) processes to track cables among a tangled bundle of cables are provided. An AR method, according to one implementation, includes a step of obtaining an initial captured image showing a bundle of cables. The AR method also includes the step of processing the initial captured image to distinguish a selected cable from other cables of the bundle of cables. Also, the AR method includes displaying the initial captured image on a display screen while visually augmenting an image of the selected cable to highlight the selected cable with respect to the other cables.