Described here are systems and methods for optimization techniques for automatically selecting x-ray beam spectra, energy threshold, energy bin settings, and other imaging technique parameters for photon-counting detector computed tomography (“PCCT”). The techniques described here are generally based on subject or object size, material of interest, and location of the target material. Advantageously, the optimizations can be integrated with different PCCT systems to automatically select optimal imaging technique parameters before scanning a particular subject or object.

Systems and methods are described herein for tracking, localization or controlling an elongate instrument or other medical instrument in an image or patient.

The present disclosure is related to systems and methods for image processing. The method may include obtaining an image including at least one of a first type of artifact or a second type of artifact. The method may include determining, based on a trained machine learning model, at least one of first information associated with the first type of artifact or second information associated with the second type of artifact in the image. The trained machine learning model may include a first trained model and a second trained model. The first trained model may be configured to determine the first information. The second trained model may be configured to determine the second information. The method may include generating a target image based on at least part of the first information and the second information.

A list mode image reconstruction method includes a step of dividing list mode data into a plurality of subsets and a step of acquiring a subset balance coefficient based on the number of events in the plurality of subsets.

An X-ray diagnosis apparatus according to an embodiment includes processing circuitry configured: to detect an element from X-ray image data taken of an examined subject; to determine a parameter of multi-frequency processing on the basis of a detection result of the element; and to execute the multi-frequency processing on one or both of the X-ray image data and another piece of X-ray image data taken later than the X-ray image data, on the basis of the determined parameter.

According to one embodiment, an X-ray diagnostic apparatus includes an X-ray irradiator, a scatterer, a grid, and a detector. The X-ray irradiator irradiates X-rays. The scatterer is provided between the X-ray irradiator and an object, that scatters the irradiated X-rays. The grid is provided between the scatterer and the object, that transmits the scattered X-rays within a predetermined angular range. The detector detects X-rays transmitted through the object together with an incident angle of the X-rays.

The present invention relates to a device (1) for fractional flow reserve determination. The device (1) comprises a model generator (10) configured to generate a three-dimensional model (3DM) of a portion of an imaged vascular vessel tree (VVT) surrounding a stenosed vessel segment (SVS), based on a partial segmentation of the imaged vascular vessel tree (VVT). Further, the device comprises an image processor (20) configured to calculate a blood flow (Q) through the stenosed vessel segment (SVS) based on an analysis of a time-series of X-ray images of the vascular vessel tree (VVT). Still further, the device comprises a fractional-flow-reserve determiner (30) configured to determine a fractional flow reserve (FFR) based on the three-dimensional model (3DM) and the calculated blood flow.

An image processing apparatus includes a feature extraction unit, a reconstruction unit, an evaluation unit, and a control unit. The feature extraction unit inputs an input image to a feature extraction NN, and outputs an intermediate image from the feature extraction NN. The reconstruction unit inputs the intermediate image to an m-th reconstruction NN, and outputs an m-th output image from the m-th reconstruction NN. The evaluation unit obtains an evaluation value based on a sum of differences between the m-th tomographic image and the m-th output image. The control unit repeatedly performs processes of the feature extraction unit and the reconstruction unit, calculation of the evaluation value by the evaluation unit, and training of the feature extraction NN and the m-th reconstruction NN based on the evaluation value.

A method and system for providing improved timing calibration information for use with apparatuses performing Time of Flight Positron Emission Tomography scans. Relative timing offset, including timing walk, within a set of processing units in the scanner are obtained and corrected using a stationary limited extent positron-emitting source, and timing offset between the set of processing units is calibrated using an internal radiation source, for performing calibration.

A computer-implemented method for modifying X-ray projection images of a subject region includes: generating a set of combined two-dimensional (2D) projections of a subject region, wherein each combined 2D projection includes one or more mask-bordering pixels and one or more mask-edge pixels; forming a three-dimensional (3D) matrix of the set of combined 2D projections; based on the 3D matrix, generating a linear algebraic system for determining pixel values for pixels indicated in a set of 2D projection metal masks, wherein a first change in slope of pixel value associated with a mask-edge pixel of a combined 2D projection is constrained to equal a second change in slope of pixel value associated with a mask-bordering pixel of a combined 2D projection; determining values for a variable vector of the linear algebraic system; and generating a set of inpainted 2D projections by modifying initial 2D projections with values for the variable vector.