Abstract: In some embodiments, a method comprises: obtaining a 2D ultrasound image of an imaged region of a subject, the imaged region comprising bone; identifying model template cross-sections of a 3D model of the bone corresponding to the 2D image at least in part by registering the 2D ultrasound image to the 3D model, wherein the model template cross-sections are defined prior to obtaining such 2D image, the model template cross-sections having size and shape representative of a population of potential subjects; identifying at least one location of at least one landmark feature of the bone in the 2D image based on results of the registration; and generating a visualization that includes: a visualization of the 2D image and a visualization of one of the identified cross-sections of the 3D model, wherein the visualization indicates the at least one location of the at least one landmark feature.

Abstract: A medical image processing device includes: a memory; and a processor including hardware.

Abstract: Systems and techniques for determining degree of motion using machine learning to improve medical image quality are presented. In one example, a system generates, based on a convolutional neural network, motion probability data indicative of a probability distribution of a degree of motion for medical imaging data generated by a medical imaging device. The system also determines motion score data for the medical imaging data based on the motion probability data.

Abstract: A composite information bearing device comprising an image pattern and a human readable data device. The human readable data device includes a set of human readable data symbols representing a first set of data. The first set of data includes a first data portion and a second data portion. The image pattern represents a second set of data and comprises a third data portion. One of the first or said second data portions is to form an identification code upon combination or concatenation with said third data portion, and the other one of said first or said second data portions not forming part of said identification code is to form a verification code, the verification code being related to said identification code by a scheme of operation.

Abstract: An apparatus including an interface and a processor. The interface may be configured to receive video frames generated by a plurality of capture devices. The processor may be configured to perform operations to detect objects in the video frames received from a first of the capture devices, determine depth information corresponding to the objects detected, determine blending lines in response to the depth information, perform video stitching operations on the video frames from the capture devices based on the blending lines and generate panoramic video frames in response to the video stitching operations. The blending lines may correspond to gaps in a field of view of the panoramic video frames. The blending lines may be determined to prevent the objects from being in the gaps in the field of view. The panoramic video frames may be generated to fit a size of a display.

Abstract: Methods and systems are provided for adaptive scan control. In one embodiment, a method includes, upon a first injection of a contrast agent, processing acquired projection data of a monitoring area of a subject to measure a contrast signal of the contrast agent, determining when each of a plurality of zones of a contrast scan are estimated to occur based on the contrast signal, generating a scan prescription for the contrast scan based on when each of the plurality of zones are estimated to occur, and upon a second injection of contrast agent, performing the contrast scan according to the scan prescription.

Abstract: A method for generating a panoramic image of a patient includes obtaining a digital 3D surface representation of at least a part of the patient's teeth; using the obtained digital 3D surface representation to define a customized path following the arch form of the patient's teeth; obtaining a plurality of x-ray images of at least a part of one of the patient's jaws and/or teeth; and generating the panoramic image of the patient using the customized path.

Abstract: A people flow analysis apparatus includes an acquisition unit configured to acquire positions of persons from each of a plurality of images captured by a plurality of image capturing devices, a counting unit configured to integrate the positions of the persons in each of the plurality of images and count the number of persons on a region-by-region basis, and a display unit configured to display on a map an image expression based on the number of persons counted on the region-by-region basis.

Abstract: Femoral version impacts the long-term functioning of the femoroacetabular joint. Accurate measurements of version are required for success in total hip arthroplasties and hip reconstructive surgeries. An automated algorithm is provided for identifying the major landmarks of the femur. These landmarks are then used to identify proximal axes and create a statistical shape model of the proximal femur. With six proximal axes selected, and 200 parameters (distances and angles between points) from the shape model measured, the best-fitting linear correlation is found. The difference between true version and version predicted by this model was 0.00°±5.13° with a maximum overestimation and underestimation of 11.80° and 15.35°, respectively. This model and its prediction of femoral version are a substantial improvement over pre-operative 2D or intra-operative visual estimation measures. Acetabular orientation is also determined by an automated algorithm using radii of curvature measurements.

Abstract: A computer-implemented method for autonomous segmentation of contrast-filled coronary artery vessels includes receiving a CT scan volume representing a 3D volume of a region of anatomy that includes a pericardium; preprocessing the CT scan volume to output a preprocessed scan volume; converting the CT scan volume to three sets of two-dimensional slices; extracting a region of interest (ROI) by autonomous segmentation of the heart region as outlined by the pericardium, by means of three individually trained ROI extraction convolutional neural networks (CNN), each trained to process a particular one of the three sets of two-dimensional slices to output a mask denoting a heart region as delineated by the pericardium; combining the preprocessed scan volume with the mask to obtain a masked volume; converting the masked volume to three groups of sets of two-dimensional masked slices; and performing autonomous coronary vessel segmentation to output a mask denoting the coronary vessels.

Abstract: The present disclosure relates to advanced image processing and encoded signal processing.

Abstract: An image management device includes: an image data acquisition unit that acquires image data snapped by a visual sensor; an image snap condition acquisition unit that acquires an image snap condition applied when the image data is snapped, from a manufacturing machine and the visual sensor; an archive data creation unit that creates archive data based on the image data and the image snap condition; and an archive data storage unit that stores the archive data. The archive data creation unit creates archive data after recording the image snap condition in a file. The image management device can easily reuse image data that is snapped by the visual sensor attached to the manufacturing machine and an image snap condition of the image data.

Abstract: A processing device receives first intraoral scan data of a first segment of a dental site and second intraoral scan data of a second segment of the dental site that does not stitch to the first intraoral scan data of the first segment of the dental site. The processing device generates a first virtual model of the first segment using the first intraoral scan data, and further generates a second virtual model of the second segment using the second intraoral scan data. The processing device arranges a spatial relationship of the first virtual model and the second virtual model.

Abstract: An object detection device acquires a plurality of images captured by a camera mounted in a moving body and acquires movement information of the camera. The object detection device extracts an edge from a first image among the acquired images. The object detection device calculates a plurality of candidate points corresponding to the edge in a second image, based on the movement information and calculates candidate points corresponding to a plurality of heights as height candidates of the edge. The object detection device calculates a correlation index value between the edge and each of the plurality of candidate points and detects the candidate point with the largest correlation as a correspondence point of the edge. The object detection device detects an object at a position of the edge when the correlation index value of the detected correspondence point is equal to or smaller than a predetermined threshold.

Abstract: A system and method for automated body mass index is disclosed. The disclosed method operates within a system architecture including one or more computing devices, one or more servers, and one or more databases. A processor operating within the one or more servers executes one or more algorithms for detecting relevant features associated with a potential client's multimedia information. The method may include calculating feature values, such as abdomen circumference, face width, face height, cheekbone width, jaw width, and neck width, and the like as well as calculating the body mass index of the potential client using one or more regression algorithms. A baseline and updated BMI may be determined, and used for determining a baseline and updated value.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for computerized travel services. One of the methods includes identifying photographs using an index of photographs, the photographs being identified from the index as photographs geographically related to a point of interest or destination and having a creation timestamp corresponding to a time of the year; determining for each of the photographs, a relevancy score based at least in part on: selection success data of the photograph for image queries referring to the point of interest or destination, and references to the point of interest or destination in documents associated with the photograph; and selecting a selected photograph from the photographs based at least in part on a respective visual quality score and the respective relevancy scores, the visual quality score representing a degree of visual quality of the respective photographs.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for mapping one or more inclusions in a mineral crystal. A set of image data associated with the mineral crystal is receiving. The received set of image data is analyzed. One or more inclusions associated with the mineral crystal is identified based on the analyzed image data. The identified one or more inclusions of the mineral crystal are mapped to a tree structure representing the surface of the mineral crystal. The mapped one or more inclusions are encoded as a chain-code associated with the mineral crystal. A radial distance between a center of mass value of the mineral crystal and a center of mass value of the identified one or more inclusions is calculated and a mineral crystal fingerprint is generated.

Abstract: Based on information about a vehicle, the information can be projected and displayed onto a road surface or the like. An image projection apparatus, which projects an image, includes an acquisition unit that acquires the information about the vehicle, and an image projection unit that projects the image based on the information acquired by the acquisition unit.

Abstract: Provided are a data processing method and apparatus, an electronic device and a storage medium. The data processing method comprises: according to a reference depth value and an actual depth value of a key point of a target in an image, converting first 2D coordinates of the key point into second 2D coordinates, wherein the second 2D coordinates and the reference depth value constitute a first 3D feature of the key point; and based on the first 3D feature, obtaining a 3D posture of the target.

Abstract: An imagery processing system determines alternative pixel color values for pixels of captured imagery where the alternative pixel color values are obtained from alternative sources. A main imagery capture device, such as a camera, captures main imagery such as still images and/or video sequences, of a live action scene. Alternative devices capture imagery of the live action scene, in some spectra and form, and that alternative imagery is processed to provide user-selectable alternatives for pixel ranges from the main imagery.