An image synthesis unit of an X-ray imaging apparatus is configured to correct a synthesis target image or a transparent image based on movement information of a feature point and movement information of a pixel and generate a synthesized image by synthesizing a corrected synthesis target image and a transparent image or synthesizing a synthesis target image and a corrected transparent image.

A computer-implemented method is provided for improving live video quality. The method comprises: acquiring, using a medical imaging apparatus, a stream of consecutive image frames of a subject, and the stream of consecutive image frames are acquired with reduced amount of radiation dose; applying a deep learning network model to the stream of consecutive image frames to generate an image frame with improved quality; and displaying the image frame with improved quality in real-time on a display.

This invention provides a method to optimize an x-ray beam for more than one structure within the field of view. The preferred embodiment comprises a modular construction of a collimator comprising multiple materials of varying thickness. A first attenuation is performed by the first portion of the collimator to optimize a first anatomic feature and a second attenuation is performed by the second portion of the collimator to optimize a second anatomic feature.

Method and related system (IPS) for visualizing in particular a volume of a substance during its deposition at a region of interest (ROI). A difference image is formed from a projection image and a mask image. The difference image is then analyzed to derive more accurate motion information about a motion or shape of the substance. The method or system (IPS) is capable of operating in an iterative manner. The proposed system and method can be used for processing fluoroscopic X-ray frame acquired by an imaging arrangement (100) during an embolization procedure.

A radiographic imaging device includes: a radiation detector including plural pixels, each including a sensor portion and a switching element; a detection unit that detects a radiation irradiation start if an electrical signal caused by charges generated in the sensor portion satisfies a specific irradiation detection condition, and/or if an electrical signal caused by charges generated in a radiation sensor portion that is different from the sensor portion satisfies a specific irradiation detection condition; and a control unit that determines whether or not noise caused by external disturbance has occurred after the detection unit has detected the radiation irradiation start, and if the noise has occurred, that stops a current operation of the radiation detector, and causes the detection unit to perform detection.

An imaging system may include an imaging detector to capture an image of human tissue and a compression paddle situated apart from the imaging detector to compress the human tissue between the compression paddle and the imaging detector. A force sensor may generate a force signal indicating a measure of force applied superior to the human tissue. A movement detection circuit may filter a movement signal from the force signal indicating a measure of movement of the compressed human tissue. A movement analysis module may determine that the movement signal is beyond a movement threshold. An image correction module to perform a corrective action based upon the determination that the movement signal is beyond a movement threshold.

A system and method for constructing fluoroscopic-based three dimensional volumetric data from two dimensional fluoroscopic images including a computing device configured to facilitate navigation of a medical device to a target area within a patient and a fluoroscopic imaging device configured to acquire a fluoroscopic video of the target area about a plurality of angles relative to the target area. The computing device is configured to determine a pose of the fluoroscopic imaging device for each frame of the fluoroscopic video and to construct fluoroscopic-based three dimensional volumetric data of the target area in which soft tissue objects are visible using a fast iterative three dimensional construction algorithm.

The technology relates to a methods and systems for improving medical imaging procedures. An example method includes receiving a first set of quality metrics for a plurality of medical images acquired at a first imaging facility; receiving a second set of quality metrics for a second plurality of medical images acquired at a second imaging facility; comparing the first set of quality metrics to the second set of quality metrics; based on the comparison of the first set of quality metrics to the second set of quality metrics, generating a benchmark for at least one metric in the first set of quality metrics and the second set of quality metrics; generating facility data based on the generated benchmark and the first set of quality metrics; and sending the facility data to the first imaging facility.

The present disclosure provides a system and method for motion field generation and image correction. The method may include obtaining a plurality of first sets of magnetic resonance (MR) image data of an object generated based on a plurality of first sets of imaging sequences. The method may include obtaining a motion curve of the object. The method may include obtaining position emission tomography (PET) image data of the object generated in a scanning time period. The method may include generating one or more target motion fields corresponding to the scanning time period based on the plurality of first sets of MR image data and the motion curve. The method may include generating one or more corrected PET images by correcting, based on the one or more target motion fields, the PET image data.

The disclosure relates to PET imaging systems and methods. The systems may obtain a plurality of PET images of a subject and a CT image acquired by performing a spiral CT scan on the subject. Each gated PET image may include a plurality of sub-gated PET images. The CT image may include a plurality of sub-CT images each of which corresponds to one of the plurality of sub-gated PET images. The systems may determine a target motion vector field between a target physiological phase and a physiological phase of the CT image based on the plurality of sub-gated PET images and the plurality of sub-CT images. The systems may reconstruct an attenuation corrected PET image corresponding to the target physiological phase based on the target motion vector field, the CT image, and PET data used for the plurality of gated PET images reconstruction.