A medical image processing device of the present disclosure includes: a division unit configured to divide at least one subject image in an image; a detection unit configured to detect a blur of the subject image divided by the division unit; a correction unit configured to correct the blur of the subject image based on the subject image divided by the division unit and the blur detected by the detection unit; and a combining unit configured to combine the subject image after correction and a background image formed by a region other than the subject image.

A control device includes an image quality control unit configured to control image quality of an image for display on a basis of optical axis angle information with reference to a scope axis of an endoscope and an image signal acquired by an image sensor. The optical axis angle information is information detected by information obtained by acquiring light source angle information controlled by an imaging device.

The present disclosure relates to an image processing apparatus and method that enable suppression of a reduction in subjective image quality. Image processing is performed on each of a plurality of frame images before projection. The image processing suppresses an influence of superimposition of the plurality of frame images in a projection image in projecting each of the plurality of frame images cyclically using a corresponding one of a plurality of projection sections. The plurality of frame images is included in a moving image. The present disclosure can be applied to, for example, an image processing apparatus, an image projection apparatus, a control apparatus, an information processing apparatus, an image projection system, an image processing method, a program, or the like.

A magnetic resonance imaging system including a memory configured to store machine executable instructions, pulse sequence commands, and a first machine learning model including a first deep learning network. The pulse sequence commands are configured for controlling the magnetic resonance imaging system to acquire a set of magnetic resonance imaging data. The first machine learning model includes a first input and a first output, a processor, wherein execution of the machine executable instructions causes the processor to control the magnetic resonance imaging system to repeatedly perform an acquisition and analysis process including: acquiring a dataset including a subset of the set of magnetic resonance imaging data from an imaging zone of the magnetic resonance imaging system according to the pulse sequence commands, providing the dataset to the first input of the first machine learning model, in response to the providing, receiving a prediction of a motion artifact level of the acquired magnetic resonance imaging data from the first output of the first machine learning model, the motion artifact level characterizing a number and/or extent of motion artifacts present in the acquired magnetic resonance imaging data.

A method for jointly removing rolling shutter (RS) distortions and blur artifacts in a single input RS and blurred image is presented. The method includes generating a plurality of RS blurred images from a camera, synthesizing RS blurred images from a set of GS sharp images, corresponding GS sharp depth maps, and synthesized RS camera motions by employing a structure-and-motion-aware RS distortion and blur rendering module to generate training data to train a single-view joint RS correction and deblurring convolutional neural network (CNN), and predicting an RS rectified and deblurred image from the single input RS and blurred image by employing the single-view joint RS correction and deblurring CNN.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for deblurring an image captured by a robot-mounted camera. One of the methods comprises capturing, using a camera that is attached to an arm of a robot, an image at a first time, wherein the image exhibits motion blur, and wherein the exhibited blur was caused by movement of the arm of the robot at the first time; receiving, from a robot control system of the robot, motion data characterizing the movement of the arm of the robot at the first time; generating a motion kernel using the received motion data; and generating a deblurred image by processing the image using the motion kernel.

A method operable within an image capture device for stabilizing a sequence of images captured by the image capture device is disclosed. The method comprises, using lens based sensors indicating image capture device movement during image acquisition, performing optical image stabilization (OIS) during acquisition of each image of the sequence of images to provide a sequence of OIS corrected images. Movement of the device for each frame during which each OIS corrected image is captured is determined using inertial measurement sensors. At least an estimate of OIS control performed during acquisition of an image is obtained. The estimate is removed from the intra-frame movement determined for the frame during which the OIS corrected image was captured to provide a residual measurement of movement for the frame. Electronic image stabilization (EIS) of each OIS corrected image based on the residual measurement is performed to provide a stabilized sequence of images.

Image transformation for use in a hybrid distribution architecture with improved performance characteristics is provided herein. The hybrid distribution architecture provides content to clients via a dual source system using a central cloud service and a Content Distribution Network, which uses the cloud service as its source. A client that requests a new rendition of an image provided by a chosen source of the hybrid distribution architecture will have that request handled by the source, and the source may maintain that rendition for future provision. By allowing the client to choose the source and letting that source handle the request, rather than requiring a central service hand the request, the amount of data needed to be transmitted is reduced and the speed of provision of content, modified or not, is improved for the client.

An imaging system, such as a DBT system, capable of providing an operator of the system with information concerning the location, magnitude and direction of motion detected by the system during performance of the scan to enhance image processing. The imaging system provides the motion information to the operator directly in conjunction with the images processed by the imaging system thereby providing the operator with sufficient information for decisions regarding the need for additional images for completing the scan with the imaging system before the patient is discharged, or even before the breast is decompressed.

The present invention provides an image processing method, wherein the image processing method includes the steps of: receiving an image signal, wherein the image signal comprises a first frame and a second frame; performing motion estimation on the first frame and the second frame to generate an interpolated frame; for each of a plurality of areas of the interpolated frame, determining whether there is a block in the first frame that moves to the area, and determine whether there is a block in the second frame that moves to the area, to determine whether the area belongs to a cover area or an uncover area; and in response to a determination result indicating that the area belongs to the cover area or the uncover area, adjusting image contents of the interpolated frame.