The present disclosure relates to a system and method for generating an image. At least one processor, when executing instructions, may perform one or more of the following operations. When raw data relating to an object is retrieved, an image may be generated based thereon. A first voxel of the image is identified based a first geometric parameter relating to the first voxel; a second voxel of the image is identified based on a second geometric parameter relating to the second voxel; the image is reconstructed using an iterative reconstruction process, during which the calculation relating to the first voxel is based on the first number of sub-voxels, and the calculation relating to the second voxel is based on the second voxel.

A method and system for determining a PET image of the scan volume based on one or more PET sub-images is provided. The method may include determining a scan volume of a subject supported by a scan table; dividing the scan volume into one or more scan regions; for each scan region of the one or more scan regions, determining whether there is a physiological motion in the scan region; generating, based on a result of the determination, a PET sub-image of the scan region based on first PET data of the scan region acquired in a first mode or based, at least in part, on second PET data of the scan region acquired in a second mode; and generating a PET image of the scan volume based on one or more PET sub-images.

Various methods and systems are provided for stationary CT imaging. In one embodiment, a method for an imaging system includes activating an emitter of a plurality of emitters of a stationary distributed x-ray source unit to emit an x-ray beam toward an object within an imaging volume, where the x-ray source unit does not rotate around the imaging volume, receiving the x-ray beam at a subset of detector elements of a plurality of detector elements of one or more detector arrays, sampling the plurality of detector elements to generate a total transmission profile, an attenuation profile, and a scatter measurement, generating a scatter-corrected attenuation profile by entering the total transmission profile, the attenuation profile, and the scatter measurement as inputs to a model, and reconstructing one or more images from the scatter-corrected attenuation profile.

A computer implemented method for determining a two dimensional DRR referred to as dynamic DRR based on a 4D-CT, the 4D-CT describing a sequence of three dimensional medical computer tomographic images of an anatomical body part of a patient, the images being referred to as sequence CTs, the 4D-CT representing the anatomical body part at different points in time, the anatomical body part comprising at least one primary anatomical element and secondary anatomical elements, the computer implemented method comprising the following steps: acquiring the 4D-CT; acquiring a planning CT, the planning CT being a three dimensional image used for planning of a treatment of the patient, the planning CT being acquired based on at least one of the sequence CTs or independently from the 4D-CT, acquiring a three dimensional image, referred to as undynamic CT, from the 4D-CT, the undynamic CT comprising at least one first image element representing the at least one primary anatomical element and second image elements representing the secondary anatomical elements; acquiring at least one trajectory, referred to as primary trajectory, based on the 4D-CT, the at least one primary trajectory describing a path of the at least one first image element as a function of time; acquiring trajectories of the second image elements, referred to as secondary trajectories, based on the 4D-CT; for the image elements of the undynamic CT, determining trajectory similarity values based on the at least one primary trajectory and the secondary trajectories, the trajectory similarity values respectively describing a measure of similarity between a respective one of the secondary trajectories and the at least one primary trajectory; determining the dynamic DRR by using the determined trajectory similarity values, and, in case the planning CT is acquired independently from the 4D-CT, further using a transformation referred to as planning transformation from the undynamic CT to the planning CT, at least a part of image values of image elements of the dynamic DRR being determined by using the trajectory similarity values.

An imaging system is provided that includes a gantry defining a bore configured to accept an object to be imaged, wherein the gantry is configured to rotate about the bore. The system includes multiple detector units mounted to the gantry and configured to rotate with the gantry around the bore in rotational steps, each detector unit configured to sweep about a corresponding axis and acquire imaging information while sweeping about the corresponding axis. The system includes at least one processor operably coupled to at least one of the detector units that is configured to acquire, during an initial portion of a scan, imaging information of the object based on an initial contour and to detect an actual emission contour based on the imaging information. The processor is configured to update a scan sweep plan based on the detected actual emission contour for a remaining portion of the scan.

The present technology relates to an imaging system. The imaging system can comprise at least one processor configured to apply a projection precomputation algorithm and an x-ray tomography image reconstruction system. The projection precomputation algorithm can be configured to: generate a projection operator matrix that can be used to calculate a plurality of voxels from a plurality of projection measurements before the plurality of projection measurements is acquired and store the projection operator matrix in memory. The projection operator matrix can be at least one of: a compressed matrix, a multi-iteration projection operator matrix, and a combination thereof. The x-ray tomography image reconstruction system can be configured to apply the projection operator matrix to generate a reconstructed three-dimensional image of at least an internal portion of a selected object under a surface of the selected object when the plurality of projection measurements is acquired.

Digital Breast Tomosynthesis allows for the acquisition of volumetric mammography images. The present invention allows for novel ways of viewing such images to detect microcalcifications and obstructions. In an embodiment a method for displaying volumetric images comprises computing a projection image using a viewing direction, displaying the projection image and then varying the projection image by varying the viewing direction. The viewing direction can be varied based on a periodic continuous mathematical function. A graphics processing unit can be used to compute the projection image and bricking can be used to accelerate the computation of the projection images.

Systems and methods for joint reconstruction and segmentation of organs from magnetic resonance imaging (MRI) data are provided. Sparse MRI data is received at a computer system, which jointly processes the MRI data using a plurality of reconstruction and segmentation processes. The MRI data is processed using a joint reconstruction and segmentation process to identify an organ from the MRI data. Additionally, the MRI data is processed using a channel-wise attention network to perform static reconstruction of the organ from the MRI data. Further, the MRI data can is processed using a motion-guided network to perform dynamic reconstruction of the organ from the MRI data. The joint processing allows for rapid static and dynamic reconstruction and segmentation of organs from sparse MRI data, with particular advantage in clinical settings.

The present disclosure relates to methods, systems, and non-transitory computer readable mediums for reconstructing an image. Image data may be obtained, wherein the image data may include projection data and may be generated by an imaging device. An objective function associated with a target image may be determined based on the image data. The objective function may include a difference model, wherein the difference model may represent a difference between a projection of the target image and the image data. The difference model may be determined based on a weighting matrix, and the weighting matrix may be determined based on an extended Tam window. The target image may be reconstructed by performing a plurality of iterations based on the objective function.

An image generation method is described, comprising obtaining a plurality of 2D images through an object to be imaged, obtaining a 3D image data set of the object to be imaged, and registering the 2D images with the 3D image data set. The method then further includes defining an image reconstruction plane internal to the object, being the plane of an image to be reconstructed from the plurality of 2D images. Then, for a pixel in the image reconstruction plane, corresponding pixel values from the plurality of 2D images are mapped thereto, and the mapped pixel values are combined into a single value to give a value for the pixel in the image reconstruction plane. Another aspect of the method provides for chatter removed from the image. In a medical imaging context this can provide for “de-boned” images, allowing soft tissue to be more clearly seen.