An example method includes obtaining, a virtual model of a portion of an anatomy of a patient obtained from a virtual surgical plan for an orthopedic joint repair surgical procedure to attach a prosthetic to the anatomy; identifying, based on data obtained by one or more sensors, positions of one or more physical markers positioned relative to the anatomy of the patient; and registering, based on the identified positions, the virtual model of the portion of the anatomy with a corresponding observed portion of the anatomy.

A measurement system includes a processor. Based on information measured by a camera that takes an image of a measurement target and an auxiliary object arranged on the measurement target, the processor acquires first point cloud data representing a three-dimensional geometry of the measurement target including the auxiliary object. Based on the first point cloud data and second point cloud data that is known and that represents a three-dimensional geometry of the measurement target, the processor eliminates point cloud data of the auxiliary object from the first point cloud data. The processor compares the first point cloud data, from which the point cloud data of the auxiliary object has been eliminated, with the second point cloud data. The processor displays information relating to a result of comparison on a display device.

One aspect of the present disclosure relates to a generation method for a training dataset, comprising: capturing, by one or more processors, a target object to which a marker unit recognizable under a first illumination condition is provided; and acquiring, by the one or more processors, a first image where the marker unit is recognizable and a second image obtained by capturing the target object under a second illumination condition.

The present disclosure relates to devices, apparatus and methods of improving the accuracy of image-based assay, that uses imaging system having uncertainties or deviations (imperfection) compared with an ideal imaging system. One aspect of the present invention is to add the monitoring marks on the sample holder, with at least one of their geometric and/optical properties of the monitoring marks under predetermined and known, and taking images of the sample with the monitoring marks, and train a machine learning model using the images with the monitoring mark.

The present disclosure provides methods, computing device readable medium, devices, and systems that utilize a cheek retractor and/or a mobile device holder for case assessment and/or dental treatments. One cheek retractor includes a first and a second lip holder, both including imaging markers of a predetermined size to determine a scale of teeth of a user, where each imaging marker is located a predefined distance from the remaining imaging markers, and where the lip holder is to hold a cheek away from a mouth of a user to expose teeth of the user. A mobile device holder can include elements to receive a mobile device to capture images of the patient's teeth.

An apparatus for guiding an autonomous vehicle towards a docking station including an autonomous vehicle with a camera-based sensing system, a drive system for driving the autonomous vehicle, and a control system for controlling the drive system. The apparatus includes a docking station including a first fiducial marker and a second fiducial marker, wherein the second fiducial marker is positioned on the docking station to define a predetermined relative spacing with the first fiducial marker, wherein the control system is operable to receive an image provided by the camera-based sensing system, the image including a representation of the first and second fiducial markers, and to control the drive system so as to guide the autonomous vehicle towards the base station based on a difference between the representation of the first and second fiducial markers in the received image and the predetermined relative spacing between the first and second fiducial markers.

Embodiments of the present disclosure provide a software program that displays both a volume as images and segmentation results as surface models in 3D. Multiple 2D slices are extracted from the 3D volume. The 2D slices may be interactively rotated by the user to best follow an oblique structure. The 2D slices can “cut” the surface models from the segmentation so that only half of the models are displayed. The border curves resulting from the cuts are displayed in the 2D slices. The user may click a point on the surface model to designate a landmark point. The corresponding location of the point is highlighted in the 2D slices. A 2D slice can be reoriented such that the line lies in the slice. The user can then further evaluate or refine the landmark points based on both surface and image information.

Intelligent multi-scale image parsing determines the optimal size of each observation by an artificial agent at a given point in time while searching for the anatomical landmark. The artificial agent begins searching image data with a coarse field-of-view and iteratively decreases the field-of-view to locate the anatomical landmark. After searching at a coarse field-of view, the artificial agent increases resolution to a finer field-of-view to analyze context and appearance factors to converge on the anatomical landmark. The artificial agent determines applicable context and appearance factors at each effective scale.

An unmanned aircraft system includes a testing and calibration system that enables automated testing of movable parts of an unmanned aircraft. The testing and calibration system uses a camera-based technique to determine the position and angle of movable parts, in order to establish whether or not those parts are moving in a manner consistent with correct function.

An electronic device comprises a camera and a retaining member. The camera includes an objective portion configured to collect light from a subject, a sensor portion reversibly separable from the objective portion, and a computer configured to return an indication of alignment of the objective and sensor portions based on output of one or more optical sensor elements of the sensor portion. The retaining member is configured to couple the objective portion to the sensor portion when the objective and sensor portions are aligned and also when the objective portion is separated from the sensor portion.