An x-ray imaging apparatus and associated methods are provided to execute multi-pass imaging scans for improved quality and workflow. An imaging scan can be segmented into multiple passes that are faster than the full imaging scan. Data received by an initial scan pass can be utilized early in the workflow and of sufficient quality for treatment setup, including while the another scan pass is executed to generate data needed for higher quality images, which may be needed for treatment planning. In one embodiment, a data acquisition and reconstruction technique is used when the detector is offset in the channel and/or axial direction for a large FOV during multiple passes.

The present application provides an imaging method and system, and a non-transitory computer-readable storage medium. The imaging method comprises preprocessing projection data to obtain a predicted image of a truncated portion; performing forward projection on the predicted image to obtain predicted projection data of the truncated portion; and performing image reconstruction using the projection data obtained by forward projection and projection data of an untruncated portion.

Multimodal imaging apparatus and methods include a rotatable gantry system with multiple sources of radiation comprising different energy levels (for example, kV and MV). Fast slip-ring technology and helical scans allow data from multiple sources of radiation to be combined or utilized to generate improved images and workflows, including for IGRT. Features include large field-of-view (LFOV) MV imaging, kV region-of-interest (ROI) imaging, and scalable field-of-view (SFOV) dual energy imaging.

A radiotherapy delivery device is provided. The device includes a source of therapeutic radiation and a first detector positioned to receive radiation from the source of therapeutic radiation. The device also includes a source of imaging radiation and a second detector positioned to receive radiation from the source of imaging radiation. A collimator assembly is positioned relative to the second source of radiation to selectively control a shape of a radiation beam emitted by the second radiation source to selectively expose part or the whole of the second radiation detector. A reconstruction processor can be operatively coupled to the detector and configured to generate patient images based on radiation received by the second detector from the second source of radiation. The device is configured to move from one imaging geometry to another using all or part of the second detector.

The present application provides a method and device for obtaining a predicted image of a truncated portion, an imaging method and system, and a non-transitory computer-readable storage medium. The method for obtaining a predicted image of a truncated portion comprises preprocessing projection data to obtain, by reconstruction, an initial image of the truncated portion; and calibrating the initial image based on a trained learning network to obtain the predicted image of the truncated portion.

A computed tomography (CT) system and method is provided. The CT system is used to carry out an image improvement method in which a prior or previously-acquired patient image can be used to supplement or otherwise improve an acquired CT image, wherein the acquired projection data representative of the acquired CT image might be truncated or otherwise incomplete/insufficient to accurately and stably recover the scanned object/patient.

A method include obtaining original projection data of an object. The original projection data may be acquired by scanning the object using a radiation device from one or more projection views. The original projection data may include truncation projection data that is acquired from at least one of the one or more projection views. In each of the at least one of the one or more projection views a truncation region of the object may be located outside an FOV of the radiation device. The method may include obtaining a target S-shaped extrapolation function based on the original projection data. The method may include determining, based on the target S-shaped extrapolation function and the original projection data, extended projection data corresponding to the at least one truncation region. The method may include generating an image of the object based on the original projection data and the extended projection data.

A method of scanning parameter optimization, which method may be useful with image-guided radiation therapy (IGRT), allows for controlling exposure of a beam from an x-ray source and/or controlling the detection mechanism for an x-ray detector of imaging radiation of a radiation-delivery device based on one or more parameters of a region of interest of a patient. The one or more parameters of the region of interest may include a dimension, outer contour, density, location relative to an outlet of the beam, location relative to isocenter, location to the whole patient body, etc. Exposure of the patient to the beam may be varied via modulation of one or more scanning parameters for controlling an aspect of the beam and/or the detector to provide for targeted and or reduced radiation exposure of the patient or portion of the patient, and/or for improved quality of guiding images. The modulation may be varied depending on a view angle of the region of interest from a portion of the radiation-delivery device.

In an emission imaging method, emission imaging data are acquired for a subject using an emission imaging scanner (10) including radiation detectors (12). The emission imaging data are reconstructed to generate a reconstructed image by executing a constrained optimization program including a measure of data fidelity between the acquired emission imaging data an a reconstruct-image transformed by a data model of the imaging scanner to emission imaging data. During the reconstructing, each iteration of the constrained optimization program is constrained by an image variability constraint. The reconstructed image is displayed the reconstructed image on a display device. The emission imaging may be positron emission tomography (PET) imaging data, optionally acquired using a sparse detector array. The image variability constraint may be a constraint that an image total variation (image TV) of a latent image defined using a Gaussian blurring matrix be less than a maximum value.

The invention relates to a system for reconstructing an image of an object. The system (100) comprises means (110) providing projection data acquired by an imaging unit, like a CT system, with an FOV, means (120) generating estimated image data indicative of a part of an object (20) located outside the FOV (210), means (130) estimating virtual projection data based on virtual settings of a virtual imaging unit comprising a virtual FOV, means (140) generating fused projection data by fusing the provided projection data with the virtual projection data, and means (150) reconstructing a final image. This allows basing the reconstruction on a complete set of projection information for the object and thus providing an image with a high image quality.