Systems and methods for visualizing navigation of a medical device with respect to a target using a live fluoroscopic view. The methods include determining a level of zoom of a fluoroscope when acquiring a reference frame. The methods further include determining whether the live fluoroscopic images evidence movement of the fluoroscope relative to its position when capturing a reference frame.

Evaluating dose performance of a radiographic imaging system with respect to image quality using a phantom, a channelized hotelling observer module as a model observer, and a printer, a plaque, or an electronic display includes scanning and producing images for a plurality of sections of the phantom using the radiographic imaging system, wherein the plurality of sections represent a range of patient sizes and doses and wherein the sections of the phantom contain objects of measurable detectability. Also included is analyzing the images to determine detectability results for one or more of the contained objects within the images of the plurality of sections of the phantom, wherein the analyzing includes using a channelized hotelling observer (CHO) module as a model observer; and displaying, via the printer, the plaque, or the electronic display, a continuous detectability performance measurement function using the determined detectability results.

A method of performing a radiological biopsy and associated system includes scanning a living human subject with a CT scanner to locate coordinates of an area of potential pathology and then using the coordinates to direct synchrotron radiation to a location at, or proximat the coordinates to obtain a high-resolution image of the area of potential pathology. The CT scan is accomplished with a CT scanner such as a C-Arm, vertical or horizontal CT scanner. A synchrotron radiation source emits synchrotron radiation through the subject and is processed by a processing system. The method and system allow for concurrent or sequential scanning of the subject by the CT scanner and synchrotron radiation scanner. The resulting images provide histological resolution of areas of potential pathology.

A method and apparatus is provided that uses a deep learning (DL) network to correct projection images acquired using an X-ray source with a large focal spot size. The DL network is trained using a training dataset that includes input data and target data. The input data includes large-focal-spot-size X-ray projection data, and the output data includes small-focal-spot-size X-ray projection data (i.e., smaller than the focal spot of the input data). Thus, the DL network is trained to improve the resolution of projection data acquired using a large focal spot size, and obtain a resolution similar to what is achieved using a small focal spot size. Further, the DL network is can be trained to additional correct other aspects of the projection data (e.g., denoising the projection data).

Disclosed herein is a method comprising: obtaining a third image from a first X-ray detector when the first X-ray detector and a second X-ray detector are misaligned; determining, based on a shift between a first image and the third image, a misalignment between the first X-ray detector and the second X-ray detector when the first and second detectors are misaligned; wherein the first image is an image the first X-ray detector should capture if the first and the second detectors are aligned.

A radiation phase contrast imaging device includes an X-ray source, an X-ray detector configured to detect radiated X-rays, a plurality of gratings, an image processor configured to generate a reconstructed image from an X-ray image acquired from the X-ray detector, a display, and a controller configured or programmed to perform control to display, on the display, the X-ray image before reconstruction and the reconstructed image generated by the image processor.

Various methods and systems are provided for x-ray imaging. In one embodiment, a method comprises acquiring, with an x-ray detector tilted at an angle with respect to an x-ray source, an x-ray image, calculating the angle from the x-ray image, generating a corrected x-ray image based on the calculated angle, and displaying the corrected x-ray image. In this way, tilt artifacts caused by the x-ray detector being tilted with respect to the x-ray source may be removed from an x-ray image.

The present invention relates to a method for calibrating a collimator of X-rays and an apparatus for X-ray analysis which comprises the collimator and can carry out the method automatically.

The present disclosure is related to systems and methods for isocenter calibration. The method includes providing a phantom including a first member and a second member with a fixed position relationship. The method includes acquiring, using a first device, at least one first image of the first member of the phantom. The method includes determining, based on the at least one first image, a first position relationship between a first isocenter of the first device and the first member. The method includes acquiring, using a second device, at least one second image of the second member of the phantom. The method includes determining, based on the at least one second image and the fixed position relationship, a second position relationship between a second isocenter of the second device and the first member. The method includes determining, based on the first position relationship and the second position relationship, a third position relationship between the first isocenter and the second isocenter.

Systems, methods, and devices for medical imaging are disclosed herein. In some embodiments, a method for imaging an anatomic region includes receiving, from a detector carried by an imaging arm of an x-ray imaging apparatus, a plurality of images of the anatomic region. The images can be obtained during manual rotation of the imaging arm. The imaging arm can be stabilized by a shim structure during the manual rotation. The method can also include receiving, from at least one sensor coupled to the imaging arm, pose data of the imaging arm during the manual rotation. The method can further include generating, based on the images and the pose data, a 3D representation of the anatomic region.