A system (IPS) and related method for image processing, in particular dark-field or phase contrast imaging to reduce motion artifacts. The system comprises an input interface (IN) for receiving a series of projection images (π) acquired by an X-ray imaging apparatus (XI) of an object (OB) for a given projection direction, the imaging apparatus (XI) configured for phase-contrast and/or dark-field imaging A phase-contrast and/or dark-field image generator (IGEN) applies an image generation algorithm to compute a first image based on the series the projection images (π). A motion artifact detector (MD) detects a motion artifact in the first image. A combiner (Σ) combines, if a motion artifact is so detected, a part of the first image with a part of at least one auxiliary image to obtain a combined image. The auxiliary image was previously computed by a gated application of the image generation algorithm in respect of a subset of the series of the projection images (π). The combined image may be output at an output interface (OUT) as a motion artifact reduced image.

A signal processing method according to one aspect of the present disclosure includes obtaining compressed image data including two-dimensional image information that is obtained by compressing hyperspectral information corresponding to wavelength bands included in a target wavelength range, obtaining setting data including information designating one or more sub-wavelength ranges that are parts of the target wavelength range, and generating, based on the compressed image data, two-dimensional images corresponding to wavelength bands included in the one or more sub-wavelength ranges.

A medical image processing device a reference image that is a medical image with which boundary line information related to a boundary line that is a boundary between an abnormal region and a normal region and landmark information related to a landmark that is a characteristic structure of the subject are associated and a captured image that is the medical image captured in real time, detects the landmark from the captured image, calculates a ratio of match between the landmark included in the reference image and the landmark included in the captured image, estimates a correspondence relationship between the reference image and the captured image on the basis of the ratio of match and information regarding the landmarks included in the reference image and the captured image, and generates a superimposition image in which the boundary line associated with the reference image is superimposed on the captured image on the basis of the correspondence relationship.

An image stitching method is proposed to include: A) acquiring a plurality of segment images for a target scene, each of the segment images containing a part of a target scene; B) for two adjacent segment images, which are two of the segment images that have overlapping fields of view, comparing the two adjacent segment images to determine a stitching position for the two adjacent segment images from a common part of the overlapping fields of view; and C) stitching the two adjacent images together based on the stitching position thus determined.

An image processing apparatus is disclosed. The image processing apparatus acquires a mosaic image. The image processing apparatus generates a first demosaic image by subjecting the mosaic image to a first demosaicing process in which a neural network is used, and generates a second demosaic image by subjecting the mosaic image to a second demosaicing process that is different from the first demosaicing process. The image processing apparatus generates a composite image in which the first demosaic image and the second demosaic image are combined.

A 3D object sensing system includes an object positioning unit, an object sensing unit, and an evaluation unit. The object positioning unit has a rotatable platform and a platform position sensing unit. The object sensing unit includes two individual sensing systems which each have a sensing area. A positioning unit defines a positional relation of the individual sensing systems to one another. The two individual sensing systems sense object data of object points of the 3D object and provide the object data the evaluation unit. The evaluation unit includes respective evaluation modules for each of the at least two individual sensing systems, an overall evaluation module and a generation module.

According to one embodiment, a medical information processing apparatus includes processing circuitry configured to derive an index value with respect to noise included in data associated with magnetic resonance signals collected by each of a plurality of reception coils, adjust a degree to which noise is removed from the data associated with the magnetic resonance signals based on the derived index value, remove noise from the data associated with the magnetic resonance signals based on the adjusted degree, and perform compositing of the data associated with the magnetic resonance signals from which noise has been removed.

Diffraction-based imaging systems are described. Aspects of the technology relate to imaging systems having one or more sensors inclined at angles with respect to a sample plane. In some cases, multiple sensors may be used that are, or are not, inclined at angles. The imaging systems may have no optical lenses and are capable of reconstructing microscopic images of large sample areas from diffraction patterns recorded by the one or more sensors. Some embodiments may reduce mechanical complexity of a diffraction-based imaging system. A diffractive imaging system comprises a light source, a sample support configured to hold a sample along a first plane, and a first sensor comprising a plurality of pixels disposed in a second plane that is tilted at an inclined angle relative to the first plane. The first sensor is arranged to record diffraction images of the light source from the sample.

Temporal filtering operations may be reset for certain pixels within an image frame to reduce contribution from previous input frames to reduce ghosting and other artifacts. The resetting reduces the contribution to, for example, zero, either immediately or within a predetermined period of time (e.g., a certain number of frames). A decision regarding whether to reset temporal filtering for a pixel of the image frame may be based on a probability assigned to that pixel. The probability can be based on rules with one or more criteria. One example factor for adjusting probability is a confidence level regarding the temporal filtering decision for the pixel, in which the probability for a random reset of a pixel is based on the confidence level regarding the temporal filtering decision for those pixels.

An image processing apparatus is coupled to a plurality of image capturing devices. The image processing apparatus reduces a noise in an epi-polar image while generating a three-dimensional image from a multi view image. The image processing apparatus divides the multi view image into a flat region and a non-flat region, generates the epi-polar image from the multi view image, replaces an epi-polar line in the epi-polar image corresponding to the flat region with an average pixel value of the multi-view image, and replaces an epi-polar line in the epi-polar image corresponding to the non-flat region with a pixel value of a center-view image obtained from a centrally located image capturing device among the plurality of image capturing devices.