Abstract: A method for movement compensation during CT reconstruction, comprises calculating slice images. The calculating slice images comprising: selecting an initial movement state; calculating a reference voxel position in relation to the initial movement state; calculating a column image position of a voxel; ascertaining a changed movement state of the voxel at the column image position; calculating a changed voxel position in relation to the changed movement state; calculating a changed image position of the voxel; and using an image value of the intermediate image at the changed image position for back projection to calculate the slice images.

Abstract: A method for the artifact correction of three-dimensional volume image data of an object is disclosed. In an embodiment, the method includes receiving first volume image data via a first interface, the first volume image data being based on projection measurement data acquired via a computed tomography device, the computed tomography device including a system axis, and the first volume image data including an artifact including high-frequency first portions in a direction of a system axis and including second portions, being low-frequency relative to the high-frequency first portions, in a plane perpendicular to the system axis; ascertaining, via a computing unit, artifact-corrected second volume image data by applying a trained function to the first volume image data received; and outputting the artifact-corrected second volume image data via a second interface.

Abstract: An embodiment of the invention relates to a method for calculating an image matrix size N for reconstructing image data of an examination subject from projection data. The method includes acquiring projection data obtained during a relative rotational movement between a radiation source of a computed tomography system and the examination subject; calculating the image matrix size N as a function of an extent of an axial field of view of the computed tomography system and a sharpness value in the image data to be reconstructed; and making the calculated image matrix size available to a reconstruction unit to reconstruct the image data from the projection data acquired.

Abstract: An embodiment of the invention relates to a method for calculating an image matrix size N for reconstructing image data of an examination subject from projection data. The method includes acquiring projection data obtained during a relative rotational movement between a radiation source of a computed tomography system and the examination subject; calculating the image matrix size N as a function of an extent of an axial field of view of the computed tomography system and a sharpness value in the image data to be reconstructed; and making the calculated image matrix size available to a reconstruction unit to reconstruct the image data from the projection data acquired.

Abstract: A method for the artifact correction of three-dimensional volume image data of an object is disclosed. In an embodiment, the method includes receiving first volume image data via a first interface, the first volume image data being based on projection measurement data acquired via a computed tomography device, the computed tomography device including a system axis, and the first volume image data including an artifact including high-frequency first portions in a direction of a system axis and including second portions, being low-frequency relative to the high-frequency first portions, in a plane perpendicular to the system axis; ascertaining, via a computing unit, artifact-corrected second volume image data by applying a trained function to the first volume image data received; and outputting the artifact-corrected second volume image data via a second interface.

Abstract: A method is disclosed for reconstructing CT image data. In at least one embodiment, the method includes providing measured CT projection data p based on the CT projection data p, reconstructing first CT image data fk=1, and on the basis of the first image data fk=1 iteratively generating k+1-th CT-image data according to the formula: fk+1=fk??(Q(Pfk?p)+?R(fk)) until the standard ?fk+1?fk?2 is ?n, with the reconstruction operator Q containing a noise weighting according to Q=B·Wstatist.·H. Aside from suppressing “cone” artifacts, the proposed method of at least one embodiment indicates a significant reduction in the image noise even after a few iterations.