Minimally-invasive spinal inventions are often performed using fluoroscopic imaging methods, which can give a real-time impression of the location of a surgical instrument, at the expense of a small field of view. When operating on a spinal column, a small field of view can be a problem, because a medical professional is left with no reference vertebra in the fluoroscopy image, from which to identify a vertebra, which is the subject of the intervention. Identifying contiguous vertebrae is difficult because such contiguous vertebrae are similar in shape. However, characteristic features, which differentiate one vertebra from other vertebra, and which are visible in the fluoroscopic view, may be used to provide a reference.

A processor extracts, from an image including a plurality of structures that spatially continuously present and whose corresponding labels have a hierarchy, respective key points of the plurality of structures in association with labels of a first layer; uses the key points as nodes to derive a graph structure in which the labels of the first layer are associated with the nodes; and associates the nodes with labels of a second layer lower than the first layer by analyzing the graph structure.

A system and method for determining inclination and version of a prosthetic acetabular cup relative to a coronal radiographic plane is provided. The system and method include the identification of a coronal radiographic plane in a three dimensional medical image. The system and method further include the identification of two symmetric landmarks on the pelvis to determine a mediolateral axis. The version and inclination can then be calculated based on the relationship between the axis of the acetabular cup, the coronal radiographic plan, and the mediolateral axis.

Apparatuses, systems and methods are provided for detecting vehicle occupant actions. More particularly, apparatuses, systems and methods are provided for detecting vehicle occupant actions based on digital image data.

The present invention relates to a method and apparatus for evaluating inspiration-level quality of a chest radiographic image, wherein the method includes extracting a lung region from a chest radiographic image, detecting a rib cage from the extracted lung region, analyzing a degree of inspiration when the chest radiographic image is captured, and evaluating quality of the chest radiographic image. It is possible for the present invention to be applied to other embodiments.

A method for computer assisted identification of appropriate anatomical structure for placement of a medical device, comprising: receiving a 3D scan volume comprising set of medical scan images of a region of an anatomical structure where the medical device is to be placed; automatically processing the set of medical scan images to perform automatic segmentation of the anatomical structure; automatically determining a subsection of the 3D scan volume as a 3D ROI by combining the raw medical scan images and the obtained segmentation data; automatically processing the ROI to determine the preferred 3D position and orientation of the medical device to be placed with respect to the anatomical structure by identifying landmarks within the anatomical structure with a pre-trained prediction neural network; automatically determining the preferred 3D position and orientation of the medical device to be placed with respect to the 3D scan volume of the anatomical structure.

An apparatus and method for superimposing a teeth data image onto a face image is provided. The apparatus for superimposing the teeth data image onto the face image includes a scanner for generating a teeth data image by scanning a teeth of a patient; a camera for obtaining a side face image by photographing a side face of the patient; and a control unit for extracting a feature point of the side face image, extracting a reference line of the side face based on the feature point, adjusting a size of the teeth data image according to a length of the reference line of the side face, and superimposing the teeth data image onto the side face image.

A surgical navigation system includes: a tracker (125) for real-time tracking of a position and orientation of a robot arm (191); a source of a patient anatomical data (163) and a robot arm virtual image (166); a surgical navigation image generator (131) generating a surgical navigation image (142A) including the patient anatomy (163) and the robot arm virtual image (166) in accordance to the current position and/or orientation data provided by the tracker (125); a 3D display system (140) showing the surgical navigation image (142A).

A method for computer assisted identification of appropriate anatomical structure for placement of a medical device, comprising: receiving a 3D scan volume comprising set of medical scan images of a region of an anatomical structure where the medical device is to be placed; automatically processing the set of medical scan images to perform automatic segmentation of the anatomical structure; automatically determining a subsection of the 3D scan volume as a 3D ROI by combining the raw medical scan images and the obtained segmentation data; automatically processing the ROI to determine the preferred 3D position and orientation of the medical device to be placed with respect to the anatomical structure by identifying landmarks within the anatomical structure with a pre-trained prediction neural network; automatically determining the preferred 3D position and orientation of the medical device to be placed with respect to the 3D scan volume of the anatomical structure.

Methods and systems are described which allow a classification of first and second objects in an X-ray projection image. A respective representation and localization of both objects are determined by applying the models to match the objects in the X-ray image and a spatial relation of the classified objects is obtained. Such methods and systems take advantage of artificial intelligence.