A method of processing x-ray images comprises training an artificial neural network to process multi-spectral x-ray projections to determine composition information about an object in terms of equivalent thickness of at least one basis material. The method further comprises providing a multi-spectral x-ray projection of an object, wherein the multi-spectral x-ray projection of the object contains energy content information describing the energy content of the multi-spectral x-ray projection. The multi-spectral x-ray projection is then processed with the artificial neural network to determine composition information about the object, and then the composition information about the object is provided.

The present invention is disclosing several methods related to intra-body navigation of radiopaque instrument through natural body cavities. One of the methods is disclosing the pose estimation of the imaging device using multiple images of radiopaque instrument acquired in the different poses of imaging device and previously acquired imaging. The other method allows to resolve the radiopaque instrument localization ambiguity using several approaches, such as radiopaque markers and instrument trajectory tracking.

When two detector panels are rotationally moved around the entire circumference of a region of interest and projection images of the region of interest are captured during the rotational movement, the respective detector panels are moved along the tangential direction of the rotational movement to a position where the union of the capturing ranges of the projection images captured by the respective detector panels covers the entire region of interest. The projection images captured by the respective detector panels are used to reconstruct a transaxial image of the region of interest.

Methods and systems for assessing lung function using volumetric images obtained at inspiration and expiration. The method may include processing the first and second set of images to identify known anatomical structures of the lungs, registering the first set of images to the second set of images to match voxels of the first set of images to voxels of the second set of images as matched pairs of inspiratory and expiratory voxels, calculating a continuous probability of a lung characteristic at a location of the matched pairs of voxels, and displaying the result on a display. The method may also include classifying lung tissue at each location as normal, having air trapping without emphysema, or being emphysematous.

In some examples, a method includes receiving a medical image of at least a portion of a spine in a patient. The method includes supplying the medical image to a neural network trained using training spine images and, for each training spine image, one or more spine measurement annotations. The method includes detecting, using the neural network, five or more vertebral landmarks for each of a plurality of vertebral bodies depicted in the medical image. The method includes outputting, for at least a first vertebral body, one or more deformity measurements based on the vertebral landmarks for the first vertebral body.

Disclosed herein is a method comprising: capturing a first image of a portion of a human using an image sensor inside the human with a first beam of radiation from a radiation source outside the human, while the radiation source is at a first position relative to the image sensor; capturing a second image of the portion of the human using the image sensor with a second beam of radiation from the radiation source outside the human, while the radiation source is at a second position relative to the image sensor; wherein the first position and the second position are different, or the first beam of radiation and the second beam of radiation are different; determining a three-dimensional structure of the portion based on the first image and the second image.

Disclosed is a computer program stored in a computer readable storage medium. When the computer program is executed by one or more processors, the computer program provides a user interface for displaying a lesion readings result, and the user interface may include: lesion information comprised in medical data; and one or more findings related to the lesion information and displayed in response to a user interaction with the lesion information.

A medical scan interface feature evaluator system is operable to generate an ordered image-to-prompt mapping by selecting a set of user interface features to be displayed with each of an ordered set of medical scans. The set of medical scans and the ordered image-to-prompt mapping are transmitted to a set of client devices. A set of responses are generated by each client device in response to sequentially displaying each of the set of medical scans in conjunction with a mapped user interface feature indicated in the ordered image-to-prompt mapping via a user interface. Response score data is generated by comparing each response to truth annotation data of the corresponding medical scan. Interface feature score data corresponding to each user interface feature is generated based on aggregating the response score data, and is used to generate a ranking of the set of user interface features.

A radiation image display apparatus that constitutes a radiation imaging system includes a displayer and a hardware processor that acquires image data of a dynamic image constituted of a plurality of frame images, image data of an analysis dynamic image obtained by applying predetermined image processing to the image data of the dynamic image and image data of a related dynamic image which is related to the dynamic image or the analysis dynamic image respectively, and causes the displayer to display the related dynamic image together with the dynamic image and the analysis dynamic image.

The present disclosure relates to methods of administering [.sup.18F]-FACBC. The present disclosure also relates to use of [.sup.18F]-FACBC in methods for imaging, diagnosing and monitoring metastasis or recurrence of cancer.