Abstract: The disclosure relates to a computer-implemented method for the provision of a transformation instruction for registering a 2D image with a 3D image. The method includes: receiving the 2D image and the 3D image; generating input data based on the 2D image having contour pixels and the 3D image having contour voxels; applying a trained function to the input data for identification of contour pixels of the 2D image and contour voxels of the 3D image, wherein at least one parameter of the trained function is adjusted based on a comparison of training contour pixels with comparison contour pixels and a comparison of training contour voxels corresponding thereto with comparison contour voxels; determining the transformation instruction based on the identified contour pixels of the 2D image and the contour voxels corresponding thereto of the 3D image for registering the 2D image with the 3D image; and providing the transformation instruction.

Abstract: The disclosure relates to a computer-implemented method for the provision of a transformation instruction for registering a 2D image with a 3D image. The method includes: receiving the 2D image and the 3D image; generating input data based on the 2D image having contour pixels and the 3D image having contour voxels; applying a trained function to the input data for identification of contour pixels of the 2D image and contour voxels of the 3D image, wherein at least one parameter of the trained function is adjusted based on a comparison of training contour pixels with comparison contour pixels and a comparison of training contour voxels corresponding thereto with comparison contour voxels; determining the transformation instruction based on the identified contour pixels of the 2D image and the contour voxels corresponding thereto of the 3D image for registering the 2D image with the 3D image; and providing the transformation instruction.

Abstract: A method for determining or updating a registration between a 3D image of a region of interest and a set of at least two 2D images of the same region of interest includes selecting at least one respective contour point in the 3D image for each 2D image. A 2D position of a respective depiction of each contour point is determined in the respective 2D image. At least one condition for the registration parameters that needs to be fulfilled is determined, for each contour point, to map the respective contour point to the respective 2D position in the respective 2D image. An updated set of registration parameters is determined by solving a set of equations or an optimization problem that depends on the conditions.

Abstract: A method for determining or updating a registration between a 3D image of a region of interest and a set of at least two 2D images of the same region of interest includes selecting at least one respective contour point in the 3D image for each 2D image. A 2D position of a respective depiction of each contour point is determined in the respective 2D image. At least one condition for the registration parameters that needs to be fulfilled is determined, for each contour point, to map the respective contour point to the respective 2D position in the respective 2D image. An updated set of registration parameters is determined by solving a set of equations or an optimization problem that depends on the conditions.

Abstract: A method includes, following specification of an initial transformation as a test transformation that is to be optimized, determining a 2D gradient x-ray image and a 3D gradient dataset of the image dataset, carrying out, for each image element of the gradient comparison image, a check for selection as a contour point, and determining an environment best corresponding to a local environment of the contour point and extending around a comparison point in the gradient x-ray image for all contour points in the at least one gradient comparison image. Local 2D displacement information is determined by comparing the contour points with the associated comparison points, and motion parameters of a 3D motion model describing a movement of the target region between the acquisition of the image dataset and the x-ray image are determined from the displacement information and a registration transformation describing the registration.

Abstract: A method for registering a three-dimensional image data record of a target region of a patient with a two-dimensional x-ray image is provided.

Abstract: A method includes, following specification of an initial transformation as a test transformation that is to be optimized, determining a 2D gradient x-ray image and a 3D gradient dataset of the image dataset, carrying out, for each image element of the gradient comparison image, a check for selection as a contour point, and determining an environment best corresponding to a local environment of the contour point and extending around a comparison point in the gradient x-ray image for all contour points in the at least one gradient comparison image. Local 2D displacement information is determined by comparing the contour points with the associated comparison points, and motion parameters of a 3D motion model describing a movement of the target region between the acquisition of the image dataset and the x-ray image are determined from the displacement information and a registration transformation describing the registration.

Abstract: Methods for updating a 2D/3D registration between a three-dimensional image data set corresponding to a target area subjected to a movement and a plurality of two-dimensional projection images of the target area include: selecting a plurality of contour points along a contour, the contour being visible in a first projection image and a three-dimensional image data set registered therewith, the plurality of contour points being associated with a rigid object in the target area; determining a displacement of each contour point of the plurality of contour points between the first projection image and a successively captured second projection image; obtaining movement information for each contour point of the plurality of contour points based on the determined displacement, the movement information describing a movement of the rigid object; and updating the registration based on the obtained movement information.

Abstract: A method for registering a three-dimensional image data record of a target region of a patient with a two-dimensional x-ray image is provided.

Abstract: Methods for updating a 2D/3D registration between a three-dimensional image data set corresponding to a target area subjected to a movement and a plurality of two-dimensional projection images of the target area include: selecting a plurality of contour points along a contour, the contour being visible in a first projection image and a three-dimensional image data set registered therewith, the plurality of contour points being associated with a rigid object in the target area; determining a displacement of each contour point of the plurality of contour points between the first projection image and a successively captured second projection image; obtaining movement information for each contour point of the plurality of contour points based on the determined displacement, the movement information describing a movement of the rigid object; and updating the registration based on the obtained movement information.

Abstract: A method for recording and reconstructing a three-dimensional image dataset is proposed. A plurality of projection images are acquired under different recording geometries in relation to an object to be recorded by an X-ray apparatus, in particular a C-arm X-ray apparatus. At least two projection images are recorded for at least one recording geometry, in particular for every recording geometry. The three-dimensional image dataset is reconstructed from the project images.

Abstract: A method is disclosed for increasing the quality of computer tomographic recording series, to a computation unit and to an X-ray CT system. An embodiment of the method includes scanning a subject over a period of time which makes it possible to record at least two temporally offset projection data sets of the same recording region; transforming the projection data sets into transformation data sets for at least two spatial frequency ranges; calculating temporal compensation values of the transformation data sets for some of the spatial frequency ranges and replacing the compensated values of the transformation data sets with the calculated compensation values in new transformation data sets, projection data of congruent rays always being compared; transforming the new transformation data sets back into new projection data sets; reconstructing image data sets on the basis of the new projection data sets and representing the image data sets.

Abstract: A method is disclosed for noise reduction in images with locally different and directional noise, in particular for noise reduction in image data records of computed tomography. In at least one embodiment of the method, two image data records of an identical object region that have mutually independent noise are provided. The two image data records are decomposed by a discrete wavelet transformation into a number of frequency bands, detailed images having high frequency structures being obtained in at least two different directions. Noise images in the respective frequency bands and directions are obtained by subtracting a wavelet coefficient of the two input images. These noise images are used to estimate noise locally and as a function of direction, and on the basis of this estimate local threshold values are calculated and applied to the averaged wavelet coefficients of the input images. A result image with reduced noise is obtained after an inverse wavelet transformation.

Abstract: A method for recording and reconstructing a three-dimensional image dataset is proposed. A plurality of projection images are acquired under different recording geometries in relation to an object to be recorded by an X-ray apparatus, in particular a C-arm X-ray apparatus. At least two projection images are recorded for at least one recording geometry, in particular for every recording geometry. The three-dimensional image dataset is reconstructed from the project images.

Abstract: A method is disclosed for noise reduction in images with locally different and directional noise, in particular for noise reduction in image data records of computed tomography. In at least one embodiment of the method, two image data records of an identical object region that have mutually independent noise are provided. The two image data records are decomposed by a discrete wavelet transformation into a number of frequency bands, detailed images having high frequency structures being obtained in at least two different directions. Noise images in the respective frequency bands and directions are obtained by subtracting a wavelet coefficient of the two input images. These noise images are used to estimate noise locally and as a function of direction, and on the basis of this estimate local threshold values are calculated and applied to the averaged wavelet coefficients of the input images. A result image with reduced noise is obtained after an inverse wavelet transformation.

Abstract: A method is disclosed for noise reduction in 3D volume data records from tomographic recordings. In at least one embodiment, the method includes generating at least two statistically independent equally dimensioned 3D volume data records for the same location and situation. In at least one embodiment of the method, the at least two statistically independent 3D volume data records are respectively subjected to 3D wavelet transformation with low pass filtering and high pass filtering in the three spatial directions of the three dimensional volume data record, and a respective initial data record with wavelet coefficients is calculated. Further, correlation coefficients for identical wavelet coefficients are ascertained from the initial data records and a new wavelet data record is calculated by weighting the wavelet coefficients from at least one initial data record on the basis of the ascertained correlation coefficients for the wavelet coefficients from the initial data records.

Abstract: A method for noise reduction in imaging methods is disclosed. In at least one embodiment, two statistically independent image data records in the same situation are generated, are subjected to wavelet transformation characterized by a low-pass filter and a high-pass filter, the correlation between the independent image data records is determined from respectively corresponding wavelet coefficients, and during the back transformation, wavelet coefficients with less correlation are given a lower weighting than wavelet coefficients with greater correlation. Further, the rating of the correlations and the weighting of the wavelet coefficients during the back transformation in the case of wavelet coefficients which have been produced through a combination of high-pass and low-pass filtering are independent of the rating of the correlations and the weighting of the wavelet coefficients during the back transformation of the wavelet coefficients which have been produced through pure high-pass filtering.