Disclosed herein is an X-ray apparatus for acquiring a medical image, and a method of using said X-ray apparatus, said method comprising the steps of: acquiring an original radiation image of a target object and capturing condition information of the object; acquiring a scatter radiation image related to the original radiation image by inputting the original radiation image and the capturing condition information to a learning network model configured to estimate scatter radiation; and acquiring a scatter radiation-processed medical image from the original radiation image on the basis of the original radiation image and the scatter radiation image, wherein the learning network model configured to estimate scatter radiation is a learning network model taught using a plurality of scatter radiation images and a plurality of pieces of capturing condition information related to each of the plurality of scatter radiation images.

In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).

An inspection apparatus includes a specimen stage configured to retain a specimen, at least three imaging devices arranged in a triangular array positioned above the specimen stage, each of the at least three imaging devices configured to capture an image of the specimen, one or more sets of lights positioned between the specimen stage and the at least three imaging devices, and a control system in communication with the at least three imaging devices.

Patch partition and image processing techniques are described. In one or more implementations, a system includes one or more modules implemented at least partially in hardware. The one or more modules are configured to perform operations including grouping a plurality of patches taken from a plurality of training samples of images into respective ones of a plurality of partitions, calculating an image processing operator for each of the partitions, determining distances between the plurality of partitions that describe image similarity of patches of the plurality of partitions, one to another, and configuring a database to provide the determined distance and the image processing operator to process an image in response to identification of a respective partition that corresponds to a patch taken from the image.

Projection systems and/or methods for efficient use of light by recycling a portion of the light energy for future use are disclosed. In one embodiment, a projection display system is disclosed comprising a light source; an integrating rod that receives light from said light source at a proximal end that comprise a reflective surface which may reflecting/recycle light down said integrating rod; of reflecting light down said integrating rod; a relay optical system, said relay optical system further comprising optical elements that are capable of moving the focal plane of the projector display system; and a modulator comprising at least one moveable mirror that reflects light received from the integrating rod in either a projection direction or a light recycling direction.

In one embodiment, a computer-based method includes obtaining a first image where the first image includes one or more patterns, generating a second image that substantially removes or reduces the one or more patterns from the first image at least partially by automatically detecting the one or more patterns and a zone where the one or more patterns occur in the first image, converting the first image to frequency domain data, applying a multi-parameter filter to the frequency domain data to substantially remove or reduce the one or more patterns. The parameters may include bandwidths in a depth and azimuthal direction. The parameters may be adapted in the multi-parameter filter based on the one or more patterns. The method also includes transforming the frequency domain data to spatial domain data and outputting the second image based at least in part on the spatial domain data.

Visually interactive and iterative analysis of data patterns by a user is disclosed. One example is a system including a display module and an interaction processor. The display module displays, via an interactive graphical user interface, a visual representation of a plurality of data elements and respective data relations between the data elements, and wherein each data element is represented by pixel attributes of a pixel. The interaction processor iteratively and interactively processes analysis by a user based on identifying selection, by the user, of an arbitrarily shaped region of the visual representation, clipping the selected region by zooming in to the selected region, identifying, in the clipped region, selection of data elements of interest to the user, and prompting the display module to automatically blur visual representations of data elements different from the data elements of interest by modifying the pixel attributes of respective pixels.

Provided is an image processing apparatus for correcting blinking defect noise contained in image data generated by an image sensor. The image sensor includes a pixels arranged two-dimensionally and reading circuits configured to read a pixel value. The image processing apparatus includes: an information acquisition unit configured to acquire noise information that is defined by associating positional information of the reading circuits or positional information of each of the pixels with feature data related to the blinking defect noise caused by the reading circuits; an estimation unit configured to estimate a random noise amount in a pixel of interest based on the feature data and a random noise model for estimating the random noise amount in the pixel of interest; and a correction unit configured to correct a pixel value of the pixel of interest based on the random noise amount estimated by the estimation unit.

Techniques described herein dynamically adapt an amount of smoothing that is applied to signals of a device (e.g., positions and/or orientations of an input mechanism, positions and/or orientations of an output mechanism) based on a determined distance between an object and the device, or based on a determined distance between the object and another device (e.g., a head-mounted device). The object can comprise one of a virtual object presented on a display of the head-mounted device or a real-world object within a view of the user. The object can be considered a “target” object based on a determination that a user is focusing on, or targeting, the object. For example, the head-mounted device or other devices can sense data associated with an eye gaze of a user and can determine, based on the sensed data, that the user is looking at the target object.

One embodiment of the present invention provides an image processing method, the method comprising: acquiring a plurality of viewpoint images; generating a contrast distribution from the plurality of viewpoint images; and generating an output image by performing image processing in accordance with the contrast distribution with respect to an image based on the plurality of viewpoint images.