For imaging an object subject to a cyclic motion, two or more imaging repetitions are carried out. Each of the imaging repetitions includes a sequence of equally spaced imaging events, wherein each imaging event has an event number, which corresponds to a respective predefined imaging parameter. A cycle duration of the cyclic motion is determined, a number of events per cycle is determined based on the cycle duration and a shift number is determined at least in part randomly. For a first imaging repetition, a starting number is determined depending on the number of events per cycle and the shift number. The first imaging repetition is carried out, wherein the respective sequence is started with an imaging event, whose event number is given by the starting number.

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.

A system includes a processor circuit that receives an extraluminal image obtained without contrast. The processor circuit receives multiple additional extraluminal images obtained without contrast as an intraluminal device is moved through a body lumen of a patient. The locations of the intraluminal device are tracked and used to form a curve. The curve is overlaid over one of the extraluminal images obtained without contrast. The curve and extraluminal image are displayed to a user and modified or confirmed. The intraluminal data points acquired by the intraluminal device are then co-registered to the extraluminal image. The extraluminal image and intraluminal data are displayed to the user.

Digital subtraction angiography is used to improve the contrast of images of patient vasculature. A non-contrast image is recorded with no contrast medium injected into the patient, and then a succession of contrast images is captured after the injection of a contrast medium. The non-contrast image is successively registered to the contrast images, and then subtracted. This removes background structures, but leaves the vasculature untouched, making blood vessels easier to see. Artefacts can remain when different motion layers are present in the X-ray image (for example, the spine and the lungs). This application discusses a technique to prevent artefacts occurring when different motion layers are present in an X-ray frame or sequence.

An X-ray CT apparatus according to an embodiment includes processing circuitry. The processing circuitry collects pieces of image data in a plurality of time phases that contain at least a part of a coronary artery of a heart. The processing circuitry acquires image indexes regarding the pieces of image data. The processing circuitry extracts a set of image data from combinations of pieces of image data having a larger time interval than a predetermined time interval, of the pieces of image data, based on the image indexes in the respective pieces of image data. The processing circuitry performs fluid analysis regarding the coronary artery based on the extracted set of image data to obtain a fluid parameter regarding the coronary artery.

The present disclosure provides systems and methods for automated scan preparation and real-time monitoring/adjustment in medical imaging. The automated scan preparation may include positioning a target subject to be scanned by a medical imaging device, determining a rotation scheme of the medical imaging device, targeting a scan region of the target subject with an imaging isocenter of the medical imaging device, determining target position(s) of component(s) of the medical imaging device, performing a virtual scan, generating a reference subject model representing an internal structure of the target subject, or the like. The real-time monitoring/adjustment operations may include achieving automatic brightness stabilization, monitoring a posture of the target subject, adjusting the position of component(s) of the medical imaging device, estimating a dose distribution, monitoring a treatment of the target subject, performing a motion correction, or the like.

A motion correction method includes two steps. The first step includes a global motion correction using the bilinear warping technique and a rough delineation of the lung fields. One of the native images (low energy image, high energy image) is deformed to match the other image. In a second step, local motion corrections are applied to the globally motion corrected image by computing a proximity value in small overlapping tiles. Only tiles with a sufficient high proximity value are taken into account. The maximum shift applied in this second step is limited to a few pixels to avoid strong deformations of the native images.

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.

A method and apparatus is provided to perform material decomposition based on spectral computed tomography (CT) projection data generated using registered reconstructed images. Registration is performed in the image domain, whereas material decomposition is performed in the sinogram domain. In the sinogram domain, material decomposition can include beam-hardening corrections. For at least two energy components, CT images are reconstructed, and registration is performed among the CT images. In certain implementations, the registered images are forward projected, and material decomposition is based on the resultant forward projections. In other implementations, motion images are generated from differences between the reconstructed CT images pre- and post-registration. The projection data is then corrected using forward projections of the motion images, and material decomposition is performed using the motion-corrected projection data.

A method and a system for correcting and reconstruing a plurality of projection images based on detected patient motion. The method includes obtaining a plurality of projection images generated by a scanner. Each of the plurality of projection images includes at least three markers. Each of the at least three markers has a measured three-dimensional position and measured positions on a detector panel of the scanner in a first dimension and a second dimension. The method further includes determining a position error vector for each of the plurality of projection images based on the at least three markers in each of the plurality of projection images, the position error vector defining patient motion in the projection image. The method finally includes combining each position error vector for each of the plurality of projection images with geometric parameters associated with the scanner to derive a projection matrix for each of the plurality of projection images, and generating reconstructed images corrected for patient motion from the plurality of projection images and the projection matrix for each of the plurality of projection images.