A radiation detector includes a support table in which an attachment surface having an arc surface shape is formed, a sensor panel which has a rectangular plate shape and in which pixels that include TFTs and detect radiation are two-dimensionally arranged, a circuit board, a flexible cable, and a reduction structure. The sensor panel is attached to the attachment surface while being curved following the arc surface shape. The flexible cables connect a curved side of the sensor panel and a reading circuit board and are arranged along the curved side. The flexible cable is bent to dispose the reading circuit board at an angle of 90° with respect to the sensor panel. The reduction structure reduces a bias of a stretching force applied to the flexible cable caused by the curved side.

Provided are a multi-panel detector including a marker to accurately match images photographed on a plurality of panels, and an imaging system including the same. A detector according to an exemplary embodiment of the present invention includes: a panel unit including a first panel and a second panel disposed while partially overlapping a rear portion of an end of the first panel; at least one marker disposed between a front portion of the first panel and a front portion of the second panel; and a radiation transmitting part formed at an end of the first panel and provided with the marker.

A radiation detector has a sensor panel unit which includes two sensor panels and in which end portions of the two sensor panels are arranged to overlap each other in a thickness direction. An image processing unit acquires two projection images from the two sensor panels. A combination unit of the image processing unit performs a process related to image quality on the projection image in a case in which a tomographic image which is a diagnosis image to be used for a doctor's diagnosis is generated and does not perform the process related to image quality on the projection image in a case in which a scout image which is a confirmation image for confirming a reflected state of the subject is generated.

A medical imaging system is provided. Imaging detector columns are installed in a gantry to receive imaging information about a subject. Imaging detector columns can extend and retract radially as well as be rotated orbitally around the gantry. The system can automatically adjust setup configuration and an imaging operation based on subject shape estimation information.

Various methods and systems are provided for stationary CT imaging. In one embodiment, a method for an imaging system includes activating a plurality of emitters of a stationary distributed x-ray source unit to emit x-ray beams toward an object within an imaging volume, where the x-ray source unit does not rotate around the imaging volume, receiving attenuated x-ray beams with one or more detector arrays to form a sparse view projection dataset, where each attenuated x-ray beam generates a different view, and reconstructing an image from the sparse view projection dataset using a sparse view reconstruction method.

Detector modules, detectors and medical imaging devices are provided. One of the detector modules includes: a support and a plurality of detector sub-modules arranged on the support along an extension direction in which the support extends. Each of the detector sub-modules has a first area and a second area in the extension direction. A detecting device is disposed in the first area, and a functional module is disposed in the second area. The functional module is electrically connected to the detecting device for receiving an electrical signal from the detecting device. The plurality of detector sub-modules includes a first detector sub-module and a second detector sub-module that are arranged adjacent to each other in the extension direction, and the first area of the first detector sub-module at least partially overlaps with the second area of the second detector sub-module.

A method and apparatus is provided that uses a deep learning (DL) network together with a multi-resolution detector to perform X-ray projection imaging to provide improved resolution similar to a single-resolution detector but at lower cost and less demand on the communication bandwidth between the rotating and stationary parts of an X-ray gantry. The DL network is trained using a training dataset that includes input data and target data. The input data includes projection data acquired using a multi-resolution detector, and the target data includes projection data acquired using a single-resolution, high-resolution detector. Thus, the DL network is trained to improve the resolution of projection data acquired using a multi-resolution detector. Further, the DL network is can be trained to additional correct other aspects of the projection data (e.g., noise and artifacts).

A modular x-ray imaging system includes an application specific module, a base unit in communication with the application specific module, and a mechanical support configured to support the x-ray application specific module. The base unit and application specific module are configured to communicate by wired and/or wireless communication.

A hybrid imaging system is disclosed including an arcuate arm defining a first and a second end the arcuate arm including a first detector assembly for 2D x-ray imaging of a patient and a second detector assembly for CT imaging of the patient, wherein the imaging system includes an internal drive mechanism for rotating the arcuate arm (e.g. translating the arcuate arm along an arcuate path) around the patient.

A radiographic imaging system includes a radiographic detector having a scanning device to obtain patient identifying information. The detector is programmed to display the patient identifying information in human readable form and to access additional information about the patient stored in networked databases.