The present disclosure is related to systems and methods for reconstructing a positron emission tomography (PET) image. The method includes obtaining PET data of a subject. The PET data may correspond to a plurality of voxels in a reconstructed image domain. The method includes obtaining a motion signal of the subject. The method includes obtaining motion amplitude data. The motion amplitude data may indicate a motion range for each voxel of the plurality of voxels. The method includes determining gating data based at least in part on the motion amplitude data. The gating data may include useful percentage counts each of which corresponds to at least one voxel of the plurality of voxels. The method includes gating the PET data based on the gating data and the motion signal. The method includes reconstructing a PET image of the subject based on the gated PET data.

Methods and systems for identifying internal motion of a breast of a patient during an imaging procedure. The method may include compressing the breast of the patient in a mediolateral oblique (MLO) position. During compression of the breast, a first tomosynthesis MLO projection frame for a first angle with respect the breast is acquired and a second tomosynthesis MLO projection frame for a second angle with respect to the breast is acquired. Boundaries of the pectoral muscle are identified in the projection frames and boundary representations are generated. A difference between the first representation and the second representation is determined. A motion score is then generated based on at least the difference between the first representation and the second representation.

A method of adaption of a medical computed tomography imaging process to an individual respiration behaviour of a patient comprises: recording a respiratory movement of a patient by monitoring a respiratory surrogate, and adapting the medical computed tomography imaging process based on the recorded respiratory movement of the patient. An adaption device and a medical computed tomography imaging system are also described.

A system, device, and method for visualizing vascular structures is disclosed. According to some implementations, in order to provide further improved digital subtraction angiography, a device for visualizing vascular structures is provided that includes a data provision processor, an image processor, and an output. The data provision processor is configured to provide a first sequence of non-contrast X-ray images of a region of interest of a patient for use as raw X-ray mask images. The data provision processor is also configured to provide a second sequence of contrast X-ray images of the region of interest of a patient for use as raw X-ray live-images. The image processor is configured to perform a first spatial subtraction for the first sequence of non-contrast X-ray images resulting in a first sequence of spatial-subtracted mask images. The image processor is also configured to perform a second spatial subtraction for the second sequence of contrast X-ray images resulting in a second sequence of spatial-subtracted X-ray live-images. The image processor is further configured to perform a temporal subtraction by subtracting the spatial-subtracted mask images from the spatial-subtracted X-ray live-images resulting in a sequence of spatial-temporal subtracted X-ray live-images. The output is configured to output the sequence of spatial-temporal subtracted X-ray live-images.

The present invention relates to an X-ray imaging system (10), comprising a radiograph X-ray attenuation image acquisition unit (20), at least one sensor (30), and a processing unit (40). The radiograph X-ray attenuation image acquisition unit is configured to acquire a radiograph image of a patient. The radiograph X-ray attenuation image acquisition unit is configured to provide the radiograph image to the processing unit. The at least one sensor is configured to acquire sensor data of the patient. The at least one sensor is configured to provide the sensor data to the processing unit. The processing unit is configured to determine a magnitude and direction of movement of the patient during a time of acquisition of the radiograph image, the determination comprising utilization of the sensor data. The processing unit is configured to post-process the radiograph image comprising utilization of the determined magnitude and direction of movement of the patient during the time of acquisition of the radiograph image.

A method of sequential monoscopic tracking is described. The method includes generating a plurality of projections of an internal target region within a body of a patient, the plurality of projections comprising projection data about a position of an internal target region of the patient. The method further includes generating external positional data about external motion of the body of the patient using one or more external sensors. The method further includes generating, by a processing device, a correlation model between the projection data and the external positional data by fitting the plurality of projections of the internal target region to the external positional data. The method further includes estimating the position of the internal target region at a later time using the correlation model.

Various methods and systems are provided for x-ray imaging. In one embodiment, a method includes acquiring a plurality of fluoroscopic images depicting an interventional tool positioned relative to an anatomy of interest of a patient, segmenting the interventional tool in the plurality of fluoroscopic images, measuring motion of the patient in the plurality of fluoroscopic images, correcting the plurality of fluoroscopic images to remove the motion of the patient, registering the segmented interventional tool to the anatomy of interest in the corrected plurality of fluoroscopic images, and displaying images with the segmented interventional tool registered to the anatomy of interest. In this way, a practitioner may view the position and movement of an interventional tool located within a patient relative to static images of the anatomy without motion artifacts or errors induced by patient motion such as respiratory motion or cardiac motion.

A system and method includes determination of a region of interest of an imaging subject, generation of a first linear attenuation coefficient map of the imaging subject, the first linear attenuation coefficient map generated to associate voxels of the region of interest of the imaging subject with greater linear attenuation coefficients than voxels of other regions of the imaging subject, attenuation-correction of a plurality of tomographic frames of the imaging subject based on the first linear attenuation coefficient map to generate a second plurality of tomographic frames, and determination of tomographic inconsistency of the second plurality of tomographic frames. Some aspects further include generation of a second linear attenuation coefficient map of the imaging subject, attenuation-correction of the plurality of tomographic frames based on the second linear attenuation coefficient map to generate a third plurality of tomographic frames, and reconstruction of a three-dimensional image based on the third plurality of tomographic frames and the determined tomographic inconsistency.

A method of the present disclosure includes performing, by a processing device, a first image registration between a reference image of a patient and a motion image of the patient to perform alignment between the reference image and the motion image, wherein the reference image and the motion image include a target position of the patient. The method further includes performing, by the processing device, a second image registration between the reference image and a motion x-ray image of the patient, via a first digitally reconstructed radiograph (DRR) for the reference image of the patient. The method further includes tracking at least a translational change in the target position based on the first registration and the second registration.

A system, device and method of imaging using a real-time, AI-enabled analysis device coupled to an imaging device during an image scan of a subject includes: receiving data corresponding to a plurality of image frames from the imaging device and user input identifying a region of interest (ROI) in a first image frame; providing data corresponding to the first image frame, including the identified ROI and data corresponding to the remaining image frames to the AI-enabled data processing system; accepting a plurality of valid image frames from the plurality of image frames based on a predefined set of computer vision rules and a minimum accepted frame threshold; calculating, frame by frame, an ROI function value of the plurality of valid image frames; determining whether a predetermined ROI function value has been reached; and alerting an operator of the imaging device that the predetermined ROI function value has been reached.