An image acquisition unit acquires a plurality of projection images corresponding to a plurality of radiation source positions at the time of tomosynthesis imaging, the plurality of projection images being generated by causing an imaging apparatus to perform tomosynthesis imaging in which radiation is emitted to a subject. A structure position specifying unit specifies one structure position in the subject. A display controller specifies projection positions of the structure position in the plurality of projection images, and performs switching display of the plurality of projection images on a display unit so that the projection positions match a predetermined position on the display unit.

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 be generated by a detector array. A weighting window may be determined based on at least one parameter relating to the detector array. A first set of data may be determined based on the image data and the weighting window. An objective function associated with a target image may be determined based on the first set of data, wherein the objective function may include a first model, the first model may represent a difference between the target image and the first set of data, and the first model may be identified based on the first set of data. The target image may be reconstructed by performing a plurality of iterations based on the objective function.

Cone beam computed tomography image acquisition protocols typically acquire a series of 2D projection images around a region of interest of a patient. The time required for a C-arm to travel around an acquisition orbit around the region of interest of a patient is non-trivial, and as a result, a patient being imaged may move during the acquisition. This is problematic because many computed tomography image acquisition algorithms assume that a patient is perfectly still during the acquisition time. If patient moves as the series of 2D projection images is being obtained, a 3D reconstruction will be affected by image artefacts. This application proposes to identify and to remove image artefacts caused by the relative motion of at least two rigid objects in the region of interest (For example, a mandible moving with respect to a skull during the acquisition). The at least two rigid objects have a more predictable motion characteristic, which may be used to correct 2D images of the input projection image sequence before a final reconstruction step. Accordingly, 3D images of a patient may be provided with fewer artefacts even when a patient moves during an acquisition.

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.

The present disclosure is related to systems and methods for reconstructing a positron emission tomography (PET) image. The method includes obtaining PET data of a subject. The PET data may correspond to a plurality of voxels in a reconstructed image domain. The method includes obtaining a motion signal of the subject. The method includes obtaining motion amplitude data. The motion amplitude data may indicate a motion range for each voxel of the plurality of voxels. The method includes determining gating data based at least in part on the motion amplitude data. The gating data may include useful percentage counts each of which corresponds to at least one voxel of the plurality of voxels. The method includes gating the PET data based on the gating data and the motion signal. The method includes reconstructing a PET image of the subject based on the gated PET data.

In nuclear medical imaging, respiratory motion is corrected. Rather than pairwise estimation of motion from projection views, a sequence-based technique is used to jointly estimate parameters for a motion model across many projection views. In one approach, this sequence-based method is iteratively solved with a maximum likelihood objective function incorporating the motion model. A surrogate respiration signal is used to gate for the joint estimation and used to convert gated motion parameters to temporal motion parameters.

A method is for generating image data of an examination object via a computed tomography system including a data processing unit; an X-ray radiation source and an X-ray radiation detector suspended on a support and mounted to be rotatable about a z-axis; and an examination table for supporting the examination object and a reference object arranged in a fixed position relative to the examination table. The method includes generating a raw data set by displacing the X-ray radiation source and the X-ray radiation detector relative to the examination object. During generation of the raw data set, at least one part of the examination object is sampled together with at least one part of the reference object. The sampling of the at least one part of the reference object is used to compensate at least in part for the influence of movement errors during the displacement.

The invention provides, in some aspects, a system for implementing a rule derived basis to display volumetric image sets. In various embodiments of the invention, the selection of the images to be displayed, the generation of the 3-D volumetric image from measured 2-D images including the rendering parameters and styles, the choice of viewing directions and 2-D projection images based on the viewing directions, the layout of the projection images, and the formation of a video can be determined using a rule derived basis. In an embodiment of the present invention, the user is presented with sequential images making up a video displayed based on their preferences without having to first manually adjust parameters. The present invention allows for novel ways of viewing such images to detect microcalcifications and obstructions when reviewing Digital Breast Tomosynthesis and other volumetric mammography images.

The disclosure relates to PET imaging systems and methods. The systems may execute the methods to obtain an anatomical image and PET data of a subject, and gate the PET data into a plurality of bins. The systems may execute the methods to reconstruct a plurality of gated PET images based on the gated PET data. The systems may execute the methods to determine a motion vector field corresponding to a target respiratory phase with respect to a reference respiratory phase relating to the anatomical image. The systems may execute the methods to obtain a respiratory phase-matched anatomical image for the target respiratory phase by transforming a VOI in the anatomical image based on the motion vector field corresponding to the target respiratory phase with respect to the reference respiratory phase, and reconstructing an attenuation corrected PET image corresponding to the target respiratory phase.

Various systems and methods for generating images are provided. In some embodiments, the techniques can include acquiring a medical image and an associated motion characterization. The motion characterization can then be used to generate a plurality of gated image data sets, sorted by phase in the motion cycle. A new amplitude-based motion characterization curve is derived from the association of phases with amplitude-based characteristics in the phase gated images. This newly derived amplitude-based motion characterization curve can then be used to re-sort data according to amplitude-based gating techniques known in the field or with data driven optimization techniques.