Disclosed is an interaction system between a controller and a VR application. The interaction system includes a controller including a first actuator configured to move a mass and a first processor configured to control an operation of the first actuator; and a content execution device configured to execute an application according to a control signal received from the controller and generate a feedback signal to transmit the generated feedback signal to a controller when a virtual object change event occurs during the application execution, wherein the first processor of the controller controls the first actuator when the feedback signal is received to move the mass and move a center of gravity. According to the present disclosure, since the center of gravity and the length of the controller operated by the user in reality may be changed in linkage with a change of the virtual object displayed on the display while executing the VR application, it is possible to greatly improve the immersion and feeling of use of the user.

Provided herein is technology relating to radiology and radiotherapy and particularly, but not exclusively, to apparatuses, methods, and systems for multi-axis medical imaging of patients in vertical and horizontal positions with single or dual energy acquisition.

A computing device, method and computer program product are provided to generate synthetic images of abnormalities on the surface of an object, such as a vehicle. The synthetic images of abnormalities on the surface of an object may be utilized for training a machine learning algorithm to detect and/or classify abnormalities. In the context of a method, a respective abnormality is parametrically modeled by selecting one or more control points that satisfy parameters associated with the respective abnormality and generating a surface representative of the respective abnormality based on the one or more control points. The method also renders a synthetic image of at least a portion of the surface of the object having the respective abnormality as defined by the parametric modeling thereof. The rendering of the synthetic image includes rendering the synthetic image in accordance with a predefined lighting condition and from a predefined viewpoint.

A computing device, method and computer program product are provided to generate synthetic images of abnormalities on the surface of an object, such as a vehicle. The synthetic images of abnormalities on the surface of an object may be utilized for training a machine learning algorithm to detect and/or classify abnormalities. In the context of a method, a respective abnormality is parametrically modeled by selecting one or more control points that satisfy parameters associated with the respective abnormality and generating a surface representative of the respective abnormality based on the one or more control points. The method also renders a synthetic image of at least a portion of the surface of the object having the respective abnormality as defined by the parametric modeling thereof. The rendering of the synthetic image includes rendering the synthetic image in accordance with a predefined lighting condition and from a predefined viewpoint.

An information processing apparatus extracts colors used for an image, links each color to one of color groups including a first color group and a second color group, displays, in a first region of a UI, a representative color associated with a group, of the color groups, to which extracted color is linked, displays a color palette including one color in a second region of the UI, and replaces a color included in the image and belonging to the color group associated with the selected representative color with a color selected from the color palette. If the color groups include groups to which at least one extracted color is linked, representative colors respectively associated with the groups to which at least one of the extracted colors is linked are displayed in the first region.

The present disclosure provides systems and methods for hybrid imaging. The systems and methods may obtain a first magnetic resonance (MR) image of a target object. The first MR image may be acquired by a magnetic resonance imaging (MRI) device using a first imaging sequence. The systems and methods may also obtain a second MR image of the target object. The second MR image may be acquired by the MRI device using a second imaging sequence. The second MR image may correspond to a target respiratory phase of the target object. The systems and methods may also obtain a target emission computed tomography ECT) image of the target object. The target ECT image may correspond to the target respiratory phase. The systems and methods may further fuse, based on the second MR image, the first MR image and the target ECT image.

Systems/techniques that facilitate AI-based region-of-interest masks for improved data reconstructions are provided. In various embodiments, a system can access a set of two-dimensional medical scan projections. In various aspects, the system can generate a set of two-dimensional region-of-interest masks respectively corresponding to the set of two-dimensional medical scan projections. In various instances, the system can generate a region-of-interest visualization based on the set of two-dimensional region-of-interest masks and the set of two-dimensional medical scan projections. In various cases, the system can generate the set of two-dimensional region-of-interest masks by executing a machine learning segmentation model on the set of two-dimensional medical scan projections.

A method for image reconstruction from plural copies, the method including receiving a series of measured projections p.sub.i of a target object h and associated background; iteratively reconstructing images h.sub.i(k) of the target object and images g.sub.i(k) of the background of the target object for each member i of the series of the measured projections p.sub.i over plural iterations k; and generating a final image of the target object h, based on the reconstructed images h.sub.i, when a set condition is met. The index i describes how many elements are in the series of projections p.sub.i, and iteration k indicates how many times the reconstruction of the image target is performed.

An image processing apparatus, an image processing method, a program, and a recording medium storing the program capable of extracting, from an input first image group, an image similar to an image extracted from a reference image group are provided. A first image group including a plurality of images of a user is transmitted to an order reception server. A second image group similar to the first image group is searched from a plurality of reference image groups stored in the order reception server. An image similar to an image previously extracted from the second image group is extracted from the first image group. An album is generated by arranging the image extracted from the first image group in a layout similar to a layout of an album generated from the second image group.

Adaptive recoloring of displayed digital content automatically pursues specified active color palette goals while adhering to specified active color palette constraints. Source code editors, word processors, and other programs are enhanced by adaptive recoloring. Recoloring rules may specify coloring roles, colors, tolerances, color spaces, metrics, and other criteria. Recoloring may be triggered by a zoom or another change in user focus, by a brightness change, a screen size change, by notice of a user perception change, or by another event. Recoloring improves text legibility, assists user focus, compensates for differences in color perception and emotional impact, and increases color availability without degrading usability, for example. Transitions between words or other display items can be heightened. Branding colors may be preserved, in logos and text. Automatic selections may be overridden by a user command or by interactive tuning, with warnings given as appropriate.