A system and method for reconstructing locations of sensors in radiopaque images may estimate sensor locations in two groups of good radiographic images and use them to estimate candidate sensor locations in a group of bad radiographic images B1, . . . , Bn in which many sensors are indiscernible. A first iterative process pervading from the first image B1 to the last image Bn may determine a first set of candidate sensor locations, and a second iterative process pervading from the last image Bn to the first image B1 may determine a second set of candidate sensor location for each image. Location of a sensor in each image Bi may be estimated based on the pertinent first and second candidate sensor locations related, or determined for, the particular sensor in the particular image. Sensor locations still missing in the series of images are, then, estimated using the already estimated sensor locations.

Systems and methods for synthetic medical image generation in accordance with embodiments of the invention are illustrated. One embodiment includes a synthetic medical image generation system, including a processor, and a memory containing an image synthesis application, where the image synthesis application directs the processor to obtain source image data generated by at least one medical imaging device, where the source image data describes a functional medical image taken of a patient administered with a first imaging agent, and synthesize a predicted medical image of the patient that depicts the patient as if they were administered with a second imaging agent, wherein the first imaging agent and the second imaging agent are different imaging agents.

An X-ray CT system according to an embodiment includes processing circuitry configured to: execute first scanning of acquiring a first subject data set corresponding to first X-ray energy by irradiating a first region of a subject with X-rays; execute, after the first scanning, second scanning of acquiring a second subject data set corresponding to second X-ray energy and a third subject data set corresponding to third X-ray energy different from the second X-ray energy by irradiating a second region included in the first region with X-rays; and perform material decomposition among a plurality of reference materials based on: a fourth subject data set obtained based on the first subject data set and one of the second subject data set and the third subject data set; and the other of the second subject data set and the third subject data set.

Systems and methods for processing electronic imaging data obtained from medical imaging procedures, with use of trained artificial intelligence (AI) models, are disclosed herein. In an example, a use of a medical evaluation workflow involving an AI model includes: obtaining image data and non-image data associated with a medical imaging study; using at least one AI model to analyze the image data, with the trained AI model being validated with a defined governance standard to identify a characteristic or particular type of characteristic; identifying the characteristic with the AI model; and communicating the identified characteristic to a location associated with evaluation of the medical imaging study.

A body thickness conversion unit converts a body thickness from a distance image imaged by a distance measurement camera to acquire the body thickness. A setting unit sets a gradation transformation function for use in gradation transformation processing to a radiographic image corresponding to the body thickness. A radiographic image acquisition unit acquires the radiographic image output from a radiation detector in radioscopy. A gradation transformation processing unit starts the gradation transformation processing with the gradation transformation function set by the setting unit.

An X-ray detector unit is disclosed. In an embodiment, the X-ray detector unit includes: at least one analysis unit to process electrical signals delivered from a coupled converter unit and operatable by an operating voltage; an adjustable voltage supply, coupled to the at least one analysis unit, to provide an adjustable supply voltage; an identification unit, assigned to the at least one analysis unit, to provide identification information about the at least one analysis unit in a readable manner; and a communication unit, coupled to the adjustable voltage supply, to read the identification information provided from the identification unit, and based upon the identification information provided, to adjust the adjustable voltage supply to equate the provided supply voltage to the operating voltage of the at least one analysis unit.

An X-ray image processing method, including obtaining a first X-ray image of an object including a plurality of materials including a first material and a second material different from the first material; obtaining three-dimensional (3D) information about the object using a 3D camera; obtaining first information about a thickness of the object based on the 3D information; and obtaining second information related to a stereoscopic structure of the first material by decomposing the first material from the object using the first information and the first X-ray image.

A system that comprises an X-ray imaging device for capturing an X-ray image on an imaging film, and a device for reading out said imaging film. The imaging film includes an optically readable marking, and the X-ray imaging device and/or the readout device includes a device for reading information stored on the data carrier, the data device being designed to register the optically readable marking using said readout device. A method for providing information for a readout device is also disclosed.

A spectral X-ray imaging system (100) includes an X-ray source (110) and an X-ray detector (120) that are mounted to a support structure (150). The support structure (150) is configured to rotate the X-ray source (110) and the X-ray detector (120) around two or more orthogonal axes (A-A′, B-B′). One or more processors (130) are configured to cause the system (100) to perform operations that include: generating a spectral image based on the spectral image data; and identifying, in the spectral image, a position of a first fiducial marker (180i) comprising a first material, based on a first X-ray absorption k-edge energy value (190i) of the first material.

A system includes a storage device storing a set of instructions and at least one processor in communication with the storage device, wherein when executing the instructions, the at least one processor is configured to cause the system to determine a first scan area on a scanning object. The system may also acquire raw data generated by scanning the first scan area on the scanning object and generate a positioning image based on the raw data. The system may also generate a pixel value distribution curve based on the positioning image, and determine a second scan area on the scanning object based on the pixel value distribution curve. The system may also scan the second scan area on the scanning object.